Marketing Research

2013
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Ishwar Rajput DIEMS A’BAD 30/04/2013

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 ROLE OF RESEARCH IN BUSINESS DECISION MAKING

Definition Some of the definitions of Research are: 1. Redman and Mory define research as a “systematized effort to gain new knowledge”. 2. Some people consider research as a movement, a movement from known to unknown. It is actually a voyage to discovery. Characteristics of Research a. Systematic Approach Each step must of your investigation be so planned that it leads to the next step. Planning and organization are part of this approach. A planned and organized research saves your time and money. b. Objectivity It implies that True Research should attempt to find an unbiased answer to the decisionmaking problem. c. Reproducible A reproducible research procedure is one, which an equally competent researcher could duplicate, and from it deduces approximately the same results. Precise information regarding samples-methods, collection etc., should be specified. d. Relevancy It furnishes three important tasks: · It avoids collection of irrelevant information and saves time and money · It compares the information to be collected with researcher‟s criteria for action · It enables to see whether the research is proceeding in the right direction e. Control: Research is not only affected by the factors, which one is investigating but some other extraneous factors also. It is impossible to control all the factors. All the factors that we think may affect the study have to be controlled and accounted for. For Example Suppose we are studying the relationship between incomes and shopping behavior, without controlling for education and age, it will be a height of folly, since our findings may reflect the effect of education and age rather than income. Control Must Consider · All the factors, which are under control, must be varied as per the study demands · All those variables beyond the control should be recorded Structure of Research Most research projects share the same general structure. You might think of this structure as following the shape of an hourglass. The research process usually starts with a broad area of interest, the initial problem that the researcher wishes to study. For instance, the researcher could be interested in how to use computers to improve the performance of students in mathematics. But this initial interest is far too broad to study in any single research project (it might not even be addressable in a lifetime of research). The researcher has to narrow the question down to one that can reasonably be studied in a research project. This might involve formulating a hypothesis or a focus question. For

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instance, the researcher might hypothesize that a particular method of computer instruction in math will improve the ability of elementary school students in a specific district. At the narrowest point of the research hourglass, the researcher is engaged in direct measurement or observation of the question of interest.

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Once the basic data is collected, the researcher begins to try to understand it, usually by analyzing it in a variety of ways. Even for a single hypothesis there are a number of analyses a researcher might typically conduct. At this point, the researcher begins to formulate some initial conclusions about what happened as a result of the computerized math program. Finally, the researcher often will attempt to address the original broad question of interest by generalizing from the results of this specific study to other related situations. For instance, on the basis of strong results indicating that the math program had a positive effect on student performance, the researcher might conclude that other school districts similar to the one in the study might expect similar results. Importance of Research in Management Decision The role of research has greatly increased in the field of business and economy as a whole. The study of research methods provides you with the knowledge and skills you need to solve the problems and meet the challenges of today‟s modern pace of development. Three factors stimulate the interest in a scientific research to decision making. i. The manager‟s increased need for more and better information. ii. The availability of improved techniques and tools to meet this need. iii. The resulting information overload Application of Marketing Research Following are a number of examples on the applications of marketing research. They clearly bring out how marketing research has been helpful in resolving marketing problems or in identifying opportunities or the development of new products. 1. A pharmaceutical company3 carried out a study on the prescription behavior for a major brand on account of its declining sales. The study brought out interesting and even startling findings on a number of aspects such as the relationship between the sales and

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the age of the brand, its regular promotion, its core therapeutic emphasis and the role of retailers in servicing prescriptions. Prior to the study, all these aspects had been only a matter of conjecture all the while. On the basis of findings of the study, the company changed its marketing strategy. This enabled it to regain the lost market share of its brand. 2. Malayalam Manorama, which is Kerala’s largest publication group, has recently launched a monthly women‟s magazine in Hindi, Vanita. While launching this magazine, the management observed that it was convinced through market research that there was a huge vacuum in the Hindi magazine segment. This new magazine Vanita has been positioned as a partner and friend that the modern woman can identify with. The first print run of Vanita was one lakh copies. Indications are that within a short time it may become one of the popular Hindi magazines. 3. Cadbury India Limited launched Picnic from its international portfolio in February 1998. It is wrapped in vibrant colors of red, blue and yellow in conformity with its international packaging. Earlier, Cadbury India Limited commissioned a consumer research study in Mumbai. The results of this study were encouraging and showed that the Indian youth is always interested in experimenting with new food options. 4. Procter & Gamble (P&G) launched Menthol, an international vibrant of Head & Shoulders. This joins the extra-conditioning anti-dandruff shampoo of the same brand. The company conducted a market research study prior to its launch. The findings of the study indicated a distinct need for a menthol-based shampoo. The study showed that in hot and humid conditions as in India, consumers prefer a shampoo which not only removes dandruff but also provides a cool and tingling sensation to the scalp. 5. Another example4 from P&G shows how marketing research is used to identify new opportunities in the marketplace. The company was getting a lot of data on VicksVaporub. The analysis of such data revealed that the most common symptom of cold was a headache and that majority of adults typically take a pill to cure it. This disclosed an opportunity for a product that can treat the headache as well as the other symptoms. The company thus launched Action 500. It not only treated headache but also gave relief from blocked nose. Marketing research can therefore lead to the development of a new product. 6. Pepsi Foods5 has assigned great importance-to marketing research. Through research it gets systematic information about its markets and its customers. All its research is done by the IMRB. Broadly, research studies done for Pepsi Foods fall in the following three areas: i. Studies undertaken on a continuous basis like marketing tracking studies and retail audits. ii. Studies that are commissioned for specific marketing problems faced by the company. iii. Studies done from time to time as per the requirement of the company such as a study to ascertain the effectiveness of an ad campaign. On the basis of the functions we can state some of the general objectives of Managerial Research: -making objectives

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ectives

1. Innovation objectives 2. Customer satisfaction objectives

Role of Research in Important Areas Through research, an executive can quickly get a synopsis of the current scenario, which improves his information base for making sound decisions affecting future operations of the enterprise. The following are the major areas in which research plays a key role in making effective decisions. Marketing Marketing research is undertaken to assist the marketing function. Marketing research stimulates the flow of marketing data from the consumer and his environment to marketing information system of the enterprise. Market research involves the process of

This information goes to the executive in the form of data. On the basis of this data the executive develop plans and programmers. Advertising research, packaging research, performance evaluation research, sales analysis, distribution channel, etc., may also be considered in management research. Research tools are applied effectively for studies involving: 1. Demand forecasting 2. Consumer buying behavior 3. Measuring advertising effectiveness 4. Media selection for advertising 5. Test marketing 6. Product positioning 7. Product potential Marketing Research i. Product Research: Assessment of suitability of goods with respect to design and price. ii. Market Characteristics Research (Qualitative): Who uses the product? Relationship between buyer and user, buying motive, how a product is used, analysis of consumption rates, units in which product is purchased, customs and habits affecting the use of a product, consumer attitudes, shopping habits of consumers, brand loyalty, research of

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special consumer groups, survey of local markets, basic economic analysis of the consumer market, etc. iii. Size of Market (Quantitative): Market potential, total sales quota, territorial sales quota, quota for individuals, concentration of sales and advertising efforts; appraisal of efficiency, etc. iv. Competitive position and Trends Research v. Sales Research: Analysis of sales records. vi. Distribution Research: Channels of distribution, distribution costs. Vii. Advertising and Promotion Research: Testing and evaluating, advertising and promotion viii. New product launching and Product Positioning. Production Research helps you in an enterprise to decide in the field of production on:

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Some of the areas you can apply researches are:

ification

Materials The materials department uses research to frame suitable policies regarding:

buy? Human Resource Development You must be Aware that The Human Resource Development department uses research to study wage rates, incentive schemes, cost of living, employee turnover rates, employment trends, and performance appraisal. It also uses research effectively for its most important activity namely manpower planning. Solving Various Operational and Planning Problems of Business and Industry Various types of researches, e.g., market research, operations research and motivational research, when combined together, help in solving various complex problems of business and industry in a number of ways. These techniques help in replacing intuitive Business decisions by more logical and scientific decisions Government and Economic System Research helps a decision maker in a number of ways, e.g., it can help in examining the consequences of each alternative and help in bringing out the effect on economic

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conditions. Various examples can be quoted such as‟ problems of big and small industries due to various factors–up gradation of technology and its impact on lab our and supervisory deployment, effect of government‟s liberal policy, WTO and its new guidance‟s, ISO 9000/14000 standards and their impact on our exports allocation of national resources on national priority basis, etc. Social Relationships Research in social sciences is concerned with both-knowledge for self and knowledge for helping in solving immediate problems of human relations. It is a sort of formal training, which helps an individual in a better way, e.g. essionals to earn their livelihood findings. and ideas. s, in general, to generalize new theories. Conclusive Research Exploratory research gives rise to several hypotheses, which you will have to tested for drawing definite conclusions. These conclusions when tested for validity lay the structure for your decision-making. Conclusive research is used for this purpose of testing the hypotheses generated by exploratory research. Conclusive research can further be classified as:

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Descriptive Research Descriptive research as the name suggests is designed to describe something- for example, the characteristics of users of a given product; the degree to which product use varies with income, age, sex or other characteristics; or the number who saw a specific television commercial. To be of maximum benefit, a descriptive study must only collect data for a definite purpose. Your objective and understanding should be clear and specific. Descriptive studies vary in the degree to which a specific hypothesis is the guide. It allows both implicit and explicit hypotheses to be tested depending on the research problem. For Example: A cereal company may find its sales declining. On the basis of market feedback the company may hypothesis that teenage children do not eat its cereal for breakfast. A descriptive study can then be designed to test this hypothesis. Experimental Research Experimentation will refer to that process of research in which one or more variables are manipulated under conditions, which permit the collection of data, which show the effects. Thus, we can conclude that: involved in management decisions. Research lays the structure for decision-making.

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- systematic, objective, reproducible, relevance, and control. has been briefly covered. The areas include marketing, production, banking, materials, human resource development, and government. -problem definition, research design, data collection, data analysis, and interpretation of results. All these steps have been explained in detail with their key elements. of research into - exploratory, and conclusive. hypotheses; they are tested for validity by the conclusive research. -descriptive, and experimental. the experimental research establishes in a more effective manner the cause and effect relationships among variables. Basic Research 1. The U.S. Bureau all of census is the world‟s largest fact gathering agency. All its data are for use by others including market. 2. The research in an advertising agency studies the result of use of coupons versus rebate as demand stimulation tactics, but not in a specific instance or in relation to a specific client‟s purpose. 3. A study conducted by 2 professors measuring diff between high level & low performing sales representatives, relative to their job satisfaction & their job turnover. Resets were published in an article available to anyone with a problem to which findings were relevant. Applied Marketing Research 1. Hanes, Hosiery Company, found how to solve a longstanding industry problem: how to sell hosiery through super markets. Hanes conducted a series of marketing studies thank R & D with strategic insights into the required one-side product design, how to display and advertise. Result: the „L‟ Eggs brand that revolutionized marketing. 2. IBM‟s entry into PC. (Apple had moved into it earlier). This was IBM‟s biggest challenge. Q 1. Which market segment was best strategically? Q. 2. What is the ideal product? Q. 3. What is ideal dist for target market? Marketing research guided IBM‟s decision to these problems and they proved when the new PC captured major market share. Camp bell soup-They put their world favors red and white soup labels or cans for its whole life. They had periodic studies of consumer preferences. When the first sighs of the can‟s waving popularity cause in, camp bell accelerated consumer testing of its replacement. Plastic containers were perfected, which may be the way your soup is package.

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 STEPS IN RESEARCH PROCESS Research process involves important steps· Problem definition · Research proposal · Research Design · Data Collection · Data Analysis & interpretation · Report writing · Interpretation of Research Refer diagram below to understand each steps clearly The Research Process

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Let us assume that the alternative choices are clearly specified: either II or I be employed. 10 We have identified the alternative choices but not completely specified the problem. The complete problem is concerned with the criterion that will determine the superiority of the two methods. The criterion could be: · Cost · Efficiency of materials · Availability of resources, etc. There are three aspects of research problem a. The specification of units to be studied b. The identification of the particular units within the scope of study c. The specification of the kind of information to be sought. What would you like to know if information is free and without error? A complete answer to this question defines the initial research problem. It can be redefined later if some difficulty arises. Research Proposal Research proposal are necessary for all business research, it may be the internal proposal or it may be the external proposal. But research proposal is not required in case of research studies for P. hd., or paper presentation as concerned. A proposal is known as a work plan, prospectus, outline, statement of intent, or draft plan. The proposal tells us what, why, how, where, and to whom it will be done. The proposal of research is: 1. To present the management question to be researched and its importance 2. To discuss the research efforts of others who have worked on related management questions. 3. To suggest the data necessary for solving the management question and how the data will be gathered, treated, and interpreted. Research Design Data Collection -Types and Sources: Depending upon the sources utilized, whether the data has come from actual observations or from records that are kept for normal purposes, statistical data can be classified into two categories, primary and secondary. Primary Data Primary data is one, which is collected by the investigator himself for the purpose of a specific inquiry or study. Such data is original in character and is generated by surveys conducted by individuals or research institutions. Some common types of primary data are: · Demographic and socioeconomic characteristics · Psychological and lifestyle characteristics · Attitudes and opinions · Awareness and knowledge: for example, brand awareness

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· Intentions: for example, purchase intentions. While useful, intentions are not a reliable 11 indication of actual future behavior. · Motivation: a person‟s motives are more stable than his/her behavior, so motive is a better predictor of future behavior than is past behavior. Behavior Primary data can be obtained by: Communication Involves questioning respondents either verbally or in writing. This method is versatile, since you need only to ask for the information; however, the response may not be accurate. Communication usually is quicker and cheaper than observation. Observation Involves the recording of actions and is performed by either a person or some mechanical or electronic device. Observation is less versatile than communication since some attributes of a person may not be readily observable, such as attitudes, awareness, knowledge, intentions, and motivation. Observation also might take longer since observers may have to wait for appropriate events to occur, though observation using scanner data might be quicker and more cost effective. Observation typically is more accurate than communication. Personal Interviews Have an interviewer bias that mail-in questionnaires do not have. For example, in a personal interview the respondent‟s perception of the interviewer may affect the responses Questionnaire The questionnaire is an important tool for gathering primary data. Poorly constructed questions can result in large errors and invalidate the research data, so significant effort should be put into the Questionnaire Secondary Data There are several criteria that you should use to evaluate secondary data. · Whether the data is useful in the research study. · How current the data is and whether it applies to time period of interest. · Errors and accuracy - whether the data is dependable and can be verified. · Presence of bias in the data. · Specifications and methodologies used, including data collection method, response rate, quality and analysis of the data, sample size and sampling technique, and questionnaire design. · Objective of the original data collection. · Nature of the data, including definition of variables, units of measure, categories used, and relationships examined. Hypothesis Testing A basic fact about testing hypotheses is that a hypothesis may be rejected but that the hypothesis never can be unconditionally accepted until all possible evidence is evaluated.

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In the case of sampled data, the information set cannot be complete. So if a test using such data does not reject a hypothesis, the conclusion is not necessarily that the 12 hypothesis should be accepted. The null hypothesis in an experiment is the hypothesis that the independent variable has no effect on the dependent variable. The null hypothesis is expressed as H0. This hypothesis is assumed to be true unless proven otherwise. The alternative to the null hypothesis is the hypothesis that the independent variable does have an effect on the dependent variable. This hypothesis is known as the alternative, research, or experimental hypothesis and is expressed as H1. This alternative hypothesis states that the relationship observed between the variables cannot be explained by chance alone. There are two types of errors in evaluating hypotheses: · Type I error: occurs when one rejects the null hypothesis and accepts the alternative, when in fact the null hypothesis is true. · Type II error: occurs when one accepts the null hypothesis when in fact the null hypothesis is false. Because their names are not very descriptive, these types of errors sometimes are confused. Some people jokingly define a Type III error to occur when one confuses Type I and Type II. To illustrate the difference, it is useful to consider a trial by jury in which the null hypothesis is that the defendant is innocent. If the jury convicts a truly innocent defendant, a Type I error has occurred. If, on the other hand, the jury declares a truly guilty defendant to be innocent, a Type II error has occurred. Hypothesis testing involves the following steps: · Formulate the null and alternative hypotheses. · Choose the appropriate test. · Choose a level of significance (alpha) - determine the rejection region. · Gather the data and calculate the test statistic. · Determine the probability of the observed value of the test statistic under the null hypothesis given the sampling distribution that applies to the chosen test. · Compare the value of the test statistic to the rejection threshold. · Based on the comparison, reject or do not reject the null hypothesis. · Make the marketing research conclusion. In order to analyze whether research results are statistically significant or simply by chance, a test of statistical significance can be run Tests of Statistical Significance The chi-square goodness-of-fit test is used to determine whether a set of proportions have specified numerical values. It often is used to analyze vicariate cross-tabulated data. Some examples of situations that are well suited for this test are: · A manufacturer of packaged products test markets a new product and wants to know if sales of the new product will be in the same relative proportion of package sizes as sales of existing products. · A company‟s sales revenue comes from Product A (50%), Product B (30%), and Product C (20%). The firm wants to know whether recent fluctuations in these proportions are random or whether they represent a real shift in sales.

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ANOVAs Another test of significance is the Analysis of Variance (ANOVA) test. The primary 13 purpose of ANOVA is to test for differences between multiple means. Whereas the t-test can be used to compare two means, ANOVA is needed to compare three or more means. If multiple t-tests were applied, the probability of a TYPE I error (rejecting a true null hypothesis) increases as the number of comparisons increases One-way ANOVA examines whether multiple means differ. The test is called an F-test. ANOVA calculates the ratio of the variation between groups to the variation within groups (the F ratio). While ANOVA was designed for comparing several means; it also can be used to compare two means. Two-way ANOVA allows for a second independent variable and addresses interaction. To run a one-way Anova, use the following steps: · Identify the independent and dependent variables. · Describe the variation by breaking it into three parts – the total variation, the portion that is within groups, and the portion that is between groups (or among groups for more than two groups). The total variation (SStotal) is the sum of the squares of the differences between each value and the grand mean of all the values in all the groups. The in-group variation (Swathing) is the sum of the squares of the differences in each element‟s value and the group mean. The variation between group means (SSbetween) is the total variation minus the in-group variation (SStotal - Swathing). 1. Measure the difference between each group‟s mean and the grand mean. 2. Perform a significance test on the differences. 3. Interpret the results. This F-test assumes that the group variances are approximately equal and that the observations are independent. It also assumes normally distributed data; however, since this is a test on means the Central Limit Theorem holds as long as the sample size is not too small ANOVA is efficient for analyzing data using relatively few observations and can be used with categorical variables. Note that regression can perform a similar analysis to that of ANOVA. What is a Research Proposal? A proposal is an offer to produce or render a service to the potential buyer or sponsor. The research proposal presents a problem, discusses related research efforts, outlines the data needed and shows the research design. Usefulness · Sponsor uses proposal to evaluate research idea · Ensures the sponsor and investigator agree to research question · For newcomer, research proposal helps learning from others · Completed proposal provides a logical guidance Dear friends, after completion of this lesson you will be able to · Prepare internal research proposal

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· Prepare external research proposal Depending on the type of project, the sponsoring individual or institution, and the cost of 14 the project, different levels of complexity are required for a proposal to be judged complete. For example the government agencies demand the most complex proposals for their funding analyses. On the other extreme, an exploratory study done within a manager‟s department may need merely a one- to three-page memo outlining the objectives, approach, and time allotted to the project. In general, business proposals can be divided between those generated internally and externally. An internal proposal is done for the corporation by staff specialists or by the research department of the firm. External proposals are either solicited or unsolicited. Sponsors can be university grant committees, government agencies, government contractors, corporations, and so forth. With few exceptions, the larger the project, the more complex is the proposal. In public sector work, the complexity is generally greater than in a comparable private sector proposal. There are three general levels of complexity. The exploratory study is the first, most simple business proposal. More complex and common in business is the small-scale study-either an internal study or an external contract research project Now let us discuss difference internal proposal & External proposal.

Hi friends this topic prepare urself,,
Marketing research techniques: Market development research: Cool hunting – socio cultural trends, Demand Estimation research, Test marketing, Segmentation Research - Cluster analysis, Discriminate analysis. Sales forecasting – objective and subjective methods

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 SOURCES OF MARKET DATA 15 Retail Audit Consumer Panel TV Meters Diary Method Internet as a source of Data Secondary Data Sources of Secondary Data RBI Economic Survey CSO Investment Data Foreign Trade Survey Data Types of Survey Techniques Retail Audit Retail Audit is a common term in marketing research Audits The key parameters that we look at when carrying out retail audits are: In-store availability of product/brand; · Types of outlets (by owner, location, specialty); · Sales volume cross-tabbed with type and location; · Pricing of product/brand cross-tabbed with type/location of outlet; · Display value; · Customer demand; · Resulting market share and rank/position of product/ brand. It must be noted that there are no readily available retail universe data. The design of a retail audit is critical to the success of the project. The data obtained from the retail audit is useful for carrying out · Identification of market opportunities · Trend analyses and forecasting · Studying market structure · Prioritization of markets · Conducting analyses of competitors · Product portfolio analysis · Understanding changes in distribution · Pricing trend analyses · Product Categories Covered This Audit covers more than 100 product categories including · Baby products (oil, powder, diapers, milk food, weaning food.) · Beverages (coffee, soup mix, squash and juice, syrup, tea, concentrated drinks.) · Contraceptives · Cosmetics (colognes, deodorant, perfume, lipstick, nail polish.)

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· Environmental hygiene (air freshener, floor cleaner, floor polish, etc.) 16 · Fabric care (fabric bleach, washing powder, liquid, whitener, soap, detergent.) · Food products (butter, margarine, salt, packaged food, etc.) · General toiletries (mouthwash, talcum powder, toilet soap, toothpaste, toothbrush, sanitary napkins.) · Hair care (conditioner, dye, oil, shampoo.) Health products and OTC (analgesic, digestive, medicated dressing, etc.) · Liquor (beer, brandy, gin, rum, vodka, whisky, wine, liquor.) · Milk products (milk, condensed milk, milk powder, Cheese.) · Semi-durable products (batteries, bulbs, lubricants, paint, tube lights, etc.) · Shaving products (after-shaves, blades, razors, etc.) · Skin care (cream, cold cream, lotion, face-wash, etc.) · Snack foods and soft drinks (biscuits, chocolates, confectionery, etc.) Measures · Market size in terms of units sold, volume and value · Market share by volume and value · Numeric distribution · Weighted distribution · Share among handlers · Out-of-stock retailers · Per dealer off-take · Purchases by retailers · Stock levels with retailers · Stock turnover ratio · Trends for market, company, brand and SKU - for size and shares Following Steps can be followed 1. Draft the research plans and schedule, indicating. · Scope and goals; · Optimal sample size, methods of collecting quantitative & qualitative data, etc.; · Deadlines; · Structure and format of reports. 3. Fine-tuning and approval of research approach. 4. Design and production of customized research tools. 5. Launch and management of field research As a rule, we use the following field research methods: · Observation · Face-to-face POS interviews · Mystery shopping Note Do not expect data on opening stock/deliveries/closing stock, bar code data (scanning dbases), audit code levels, etc. They are mostly non-existent. 6. Data collection 7. Usually the sources can be broken down into three basic groups: a. “White area”: from official stats sources to fully legal retail;

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b. “Grey area”: includes medium and small wholesale, and kiosks (partial reporting) 17 original, but locally unauthorized product; c. “Black area”: private entrepreneurs operating without a license, ad-hoc open air markets, van sales, babushkas, etc. 8. Analysis and report writing After verification, the data are punched in (software and formats to be determined based on client needs), structured, analyzed, and presented as text, graphics, customized databases, or a combination of these.=Consumer Panel There‟s nothing (consumer) panel data can tell us that we don‟t already know from scanner data. Consumer panels are a unique tool that can enable a clever researcher to examine dynamic longitudinal changes in behaviors, attitudes, and perceptions. Consumer panels can also be an overly costly, excessive generator of unused data What are Consumer Panels? There are two basic kinds of consumer panels. In the first kind, respondents report essentially the same information repeatedly over some period of time. The chief examples of these kinds of panels are the syndicated purchase panels using store and home, termed as, continuous panels. The second kind of panel consists of samples of pre-screened respondents who report over time on a broad range of different topics, termed as discontinuous access panels. Both kinds of panels come in all different forms. Panel studies can involve data collection at widely different intervals varying anywhere from a day to several years between waves of interviews. Panel operators are continuously faced with the decision about how often panel members should be contacted and asked to report. Contacting the panel either too frequently or too infrequently may lead to reduced cooperation, The Benefits of Continuous Consumer Panels 1. The effect of a special offer can be measured through a before-and-after design using a panel approach. Thus, a sample of families might be interviewed initially to gather information on their purchases of soft drinks, possibly over several weeks to obtain a good idea of their “steady state” purchasing patterns. A special deal for a particular brand is then introduced, and the purchases of the same sample are monitored for perhaps every week for three months. In this way, sampling variation is minimized and both short-term and long-term effects of the deal are obtained. 2. A static consumer panel of families with young children might be set up to monitor the acceptance of new line of toys. In this case no type of experimental treatment is involved. Rather, information is obtained, say, every month on the toy purchases of the families. In this way, data are compiled on the types of families. \Archiving Diary Data In spite of the abundance of data derived from diary surveys across a wide range of disciplines, little is available to other researchers for secondary analysis (further analysis of data already collected). This is perhaps not surprising given that the budget for many diary surveys does not extend to systematic processing of the data. Many diary surveys

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are small-scale investigative studies that have been carried out with very specific aims in mind. For these less structured diaries, for which a common coding scheme is neither 18 feasible, nor possibly desirable, an answer to public access is to deposit the original survey documents in an archive. This kind of data bank gives the researcher access to original diary documents allowing them to make use of the data in ways to suit their own research strategy. However, the ethics of making personal documents public (even if in the limited academic sense) have to be considered. Internet as a Source of Data: The expansion of the Internet over the past decade has provided the researcher with a range of new opportunities for finding information, networking, conducting research, and disseminating research results. Through the use of tools such as online focus groups, electronic mail, and online questionnaires, the Internet opens up new possibilities for conducting research. It offers, for example: 1. Shorter timeframes for collecting and recording data: e-mail messages can be saved and analyzed in qualitative data packages, for example, while online surveys can be captured directly into a database 2. The possibility of conducting interviews and focus groups by e-mail, with related savings in costs and time 3. New “communities” to serve as the object of social scientific enquiry. 4. Opportunities for including mixed multiple media in questionnaires. On the other hand, these opportunities also raise new challenges for the researcher, Such as · Problems of sampling · The ethics of conducting research into online communities · Physical access and skills required to use the technologies involved · Accuracy and reliability of information obtained from online sources · The changed chronology of interaction resulting from asynchronous communication Internet is a useful media to get valuable information and results of various surveys. Access to computer-led data becomes handy in solving many complex mysteries, related to the market place. The 10 „C‟s outlined here, provide criteria to be considered while evaluating Internet resources: 1. Content What is the intent of the content? Are the title and author identified? Is the content “juried?” Is the content “popular” or “scholarly”, satiric or serious? What is the date of the document or article? Is the “edition” current? Do you have the latest version? (Is this important?) How do you know? 2. Credibility Is the author identifiable and reliable? Is the content credible? Authoritative? Should it be? What is the purpose of the information, that is, is it serious, satiric, and humorous? Is the URL extension .edu, .com, .gov or .org? What does this tell you about the “publisher”?

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3. Critical Thinking How can you apply critical thinking skills, including previous knowledge and experience, 19 to evaluate Internet resources? Can you identify the author, publisher, edition, etc. as you would with a “traditionally” published resource? What criteria do you use to evaluate Internet resources? 4. Copyright Even if the copyright notice does not appear prominently, someone wrote, or is responsible for, the creation of a document, graphic, sound or image, and the material falls under the copyright conventions. “Fair use” applies to short, cited excerpts, usually as an example for commentary or research. Materials are in the “public domain” if this is explicitly stated. Internet users, as users of print media, must respect copyright. 5. Citation Internet resources should be cited to identify sources used, both to give credit to the author and to provide the reader with avenues for further research. Standard style manuals (print and online) provide some examples of how to cite Internet documents, although these standards are not uniform. 6. Continuity Will the Internet site be maintained and updated? Is it now and will it continue to be free? Can you rely on this source over time to provide up-to-date information? Some good .edu sites have moved to .com, with possible cost implications. Other sites offer partial use for free, and charge fees for continued or in-depth use. 7. Censorship Is your discussion list “moderated”? What does this mean? Does your search engine or index look for all words or are some words excluded? Is this censorship? Does your institution, based on its mission, parent organization or space limitations, apply some restrictions to Internet use? Consider censorship and privacy issues when using the Internet. 8. Connectivity If more than one user will need to access a site, consider each user‟s access and “functionality.” How do users connect to the Internet and what kind of connection does the assigned resource require? Does access to the resource require a graphical user interface? If it is a popular (busy) resource, will it be accessible in the time frame needed? Is it accessible by more than one Internet tool? Do users have access to the same Internet tools and applications? Are users familiar with the tools and applications? Is the site “viewable” by all Web browsers? 9. Comparability Does the Internet resource have an identified comparable print or CD ROM data set or source? Does the Internet site contain comparable and complete information? (For example, some newspapers have partial but not full text information on the Internet.) Do you need to compare data or statistics over time? Can you identify sources for comparable earlier or later data? Comparability of data may or may not be important, depending on your project.

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10. Context What is the context for your research? Can you find “anything” on your topic, that is, 20 commentary, opinion, narrative, statistics and your quest will be satisfied? Are you looking for current or historical information Definitions? Research studies or articles? How does Internet information fit in the overall information context of your subject? Before you start searching, define the research context and research needs and decide what sources might be best to use to successfully fill information needs without data overload.

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 MARKETING MIX RESEARCH 21 1. Product Research 2. Price Research 3. Distribution Research 4. Promotion Research Product Research New Product Research New product development is critical to the life of most organizations as there will be uncertainties associated with them. Thus, the purpose of marketing research for them would reduce the uncertainties associated with the new products. Four stages of new product development could be seen: · Generating New-Product Concepts · Evaluating and Developing those Concepts · Evaluating and developing the actual products · Testing in Marketing Programmed Concept Generation There are two types of concept generation research: · Need identification research: · Concept Identification Need Identification Research The emphasis in need research is on identifying unfilled needs in the market. Following are some examples: a. Perceptual Maps, in which products are positioned along the dimensions by which users perceive and evaluate, can suggest gaps into which new products might fit. Perceptual mapping is a graphics technique used by marketers that attempts to visually display the perceptions of customers or potential customers. Typically the position of a product, product line, brand, or company is displayed relative to their competition. . Perceptual Map of Ideal Points and Clusters A company considering introducing a new product will look for areas with a high density of ideal points. They will also look for areas without competitive rivals. Placing both the ideal points and the competing products on the same map best does this. Some maps plot ideal vectors instead of ideal points. The map below, displays various aspirin products as seen on the dimensions of effectiveness and gentleness. It also shows two ideal vectors. The slope of the ideal vector indicates the preferred ratio of the two dimensions by those consumers within that segment. This study indicates there is one segment that is more concerned with effectiveness than harshness, and another segment that is more interested in gentleness than strength. Perceptual Map of Competing Products with Ideal Vectors a. Perceptual maps need not come from a detailed study. There are also intuitive maps (also called judgmental maps or consensus maps) that are created by marketers based on their understanding of their industry. Management uses its best judgments. It is

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questionable how valuable this type of map is. Often they just give the appearance of credibility to management‟s preconceptions. When detailed marketing research studies 22 are done methodological problems can arise, but at least the information is coming directly from the consumer. There is an assortment of statistical procedures that can be used to convert the raw data collected in a survey into a perceptual map. Preference regression will produce ideal vectors. Multi dimensional scaling will produce either ideal points or competitor positions. Factor analysis, discriminate analysis, cluster analysis, and legit analysis can also be used. Some techniques are constructed from perceived differences between products; others are constructed from perceived similarities. Still others are constructed from cross price elasticity of demand data from electronic scanners. b. Social and environment trends can be analyzed. c. An approach termed benefit structure analysis has product users identify the benefits desired and the extent to which the product delivers those benefits, for specific applications. The result is an identification of benefits sought that current products do not deliver. d. Product users might be asked to keep a diary of a relevant portion of their activities. Analyzing such diaries can provide an understanding of unsolved problems associated with a particular task. Types of Focus Groups Two-way focus group - one focus group watches another focus group and discusses the observed interactions and conclusions Dual moderator focus group - one moderator ensures the session progresses smoothly, while another ensures that all the topics are covered Dueling moderator focus group - two moderators deliberately take opposite sides on the issue under discussion Respondent moderator focus group - one or more of the respondents are asked to act as the moderator temporarily Client participant focus groups - one or more client representatives participate in the discussion, either covertly or overtly Mini focus groups - groups are comprised of 4 / 5 members. Telesession (or teleconference) focus groups – telephone network is used On-line focus groups - computers and internet network is used Traditional focus groups can provide accurate information, and are less expensive than other forms of traditional marketing research. There can be significant costs however : if a product is to be marketed on a nation-wide basis, it would be critical to gather respondents from various locales throughout the country since attitudes about a new product may vary due to geographical considerations. This would require a considerable expenditure in travel and lodging expenses. Additionally, the site of a traditional focus group may or may not be in a locale convenient to a specific client, so client representatives may have to incur travel and lodging expenses as well. Use Testing

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This gives the users a reasonable time to feel the product and inquires their reactions and their intentions to buy it. Researchers can contact respondents in shopping centers, by 23 personal visits to their homes or offices, or on telephone. Limitations · Due to unclear instructions, a misunderstanding, or lack of cooperation, the respondents may nor use the product correctly and may therefore report a negative opinion. · The fact that they were given a free sample and are participating in a test may distort their impressions. · Even when repurchase opportunities were made available, such decisions may be quite different than when they are made in a more realistic store situation. · The users will not accept the product over a long period of time. They may inflate their intention to buy. Consumers may say that they will buy the product but may end up not doing so. Blind-use Testing Even though a product may be proved superior in the laboratory, the consumer may not perceive it to be superior. For e.g., Amul sweets, which was perceived as a superior by the company by all standards, were introduced in the market. It was supposed to be hit during Diwali time and advertisements were released to prop up sales. Unfortunately the consumers perceived the product as a premium product and did not substitute their purchases from the local Halwai. Predicting Trial Purchase To predict trial levels of new, frequently purchased consumer products, ESP (Estimating Sales Potential) model has been developed. Trial levels were predicted on the basis of three variables: · Product class penetration (PCP), the percentage of households purchasing at least one item in the product class within one year. · Promotional expenditures-total consumer-directed promotional expenditures on the product. · Distribution of the product-percentage of stores stocking the product (weighted by the store‟s total sales volume). Pretest Marketing Two approaches are used to predict the new brand‟s market share: Preference Judgments Here the preference data are used to predict the proportion of purchases of the new brand that respondents will make given that the new brand is in their response set. These estimates for the respondents in the study are coupled with an estimate of the proportion of all people who will have the new brand in their response set., to provide an estimate of market share. This is also used to analyze the concomitant market share loses of other brands. If the firm has other brands in the market, such information can be critical. Trial and repeat purchase levels: This is based on the respondent‟s purchase decisions and intentions-to-buy judgments. A trial estimate is based on the percentage of respondents who purchase the product in the laboratory, plus an estimate of the product‟s

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distribution, advertising (which will create product awareness), and the number of free samples to be given away. The repeat purchase rate is based on the proportion of 24 respondents who make a mail order repurchase of the new brand and the buying intentions judgments of those who elected not to make a mail order repurchase. The product of the trial estimate and the repeat purchase estimate become a second estimate of market share. Test Marketing Test marketing allows the researcher to test the impact of the total marketing program, with all its interdependence, in a market context as opposed to the artificial context associated with the concept and product tests that have been discussed. Functions · To gain information and experience with the marketing program before making a total commitment to it. · To predict the program‟s outcome when it is applied to the total market. Types of Test Market · The sell-in test markets are cities in which the product is sold just as it would be in a national launch. The product has to gain distribution space. · The controlled-distribution scanner markets (CDSM) are cities for which distribution is pre-arranged and the purchases of a panel of customers are monitored using scanner data. Certain parameters that have to be looked into while deciding sell-in test market: · Representativeness: Ideally, the city should be fairly representative of the country in terms of characteristics that will affect the test outcome, such as product usage, attitudes and demographics. · Data Availability: Information about Store audit is helpful in evaluating the test. The selected cities should contain retailers who will cooperate with store audits. · Media isolation and Costs: It is desirable to avoid media spill-over. Using media that “spill-out” into nearby cities is wasteful and increases costs. Conversely, “spill-in” media from nearby cities can contaminate a test. Media cost is another consideration. · Product flow: It may be desirable to use cities that don‟t have much “product-spillage” outside the area. · Number: A single city can lead to unreliable results because of the variations across cities of both brand sales and consumer response to marketing programs. · Implementing and controlling: The test should be controlled in such a manner that it ensures the marketing program is implemented in the test area so as to reflect the national program. The test itself may tend to encourage those involved to enhance the effectiveness of the marketing program. Salespersons may be more aggressive. Retailers may be more cooperative. The competitors may react by deliberately flooding the test areas with free samples or instore promotions. Even they can retaliate or can also Monitor the results themselves. · Timing: Normally, a test market should be in existence for one year, so that all important seasonal/cultural factors can be observed and estimated.

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· Measurement: The basic measure is sales based on shipments or warehouse withdrawals. Store audit data provide actual sales figures and are not sensitive to 25 inventory fluctuations. They also provide information on: distribution, shelf-facings, and in-store promotional activity. Measures such as brand awareness, attitude, trial purchase, and repeat purchase are obtained directly from the consumer. This information helps evaluate the marketing program and can help interpret sales data. The most useful information obtained from consumers is whether they bought the product at least once, whether they were satisfied with it, and whether they repurchased it or plan to. · Costs: Costs which are quantifiable, include – development and implementation of the marketing program; preparation of test products; administration of the test and collection of data associated with the test. The costs and risks that may delay the launch of a new product are more difficult to quantify. If a new product launch is delayed, an opportunity to gain a substantial market position might be lost. Pricing Research Research may be used to evaluate alternative price approaches for new products before launch or for proposed changes in products already in the market. Pricing Approaches · Gabor and Grainger Method (Price skimming strategy), where different prices for a product are presented to respondents, who then are asked if they would buy. A “buy response” curve of different prices, with the corresponding number of affirmative purchase intentions, is produced. The objective is to generate as much profit as possible in the present period. · Multiband-choice Method (Share penetration strategy), where respondents are shown different sets of brands in the same product category, at different prices, and are asked which they would buy. Following questions are generally asked with regard to pricing research: · At what price would you consider the product to be so expensive that you would not consider buying it? (Too expensive) · At what price would you consider the product to be priced so low that you would feel the quality couldn‟t be very good? (Too cheap) · At what price would you consider the product starting to get expensive, so that it is not out of the question, but you would have to give some thought to buying it? (Expensive) · At what price would you consider the product to be a bargain-a great buy for the money? (Cheap) Research for Skimming Pricing This is based on the concept of pricing the product, at the point at which profits will be the greatest until market conditions change or supply costs dictate a price change. Under this strategy, the optimal price is the one that results in the greatest positive difference between total revenues and total costs. This implies that the researcher‟s major tasks are to forecast the costs and the revenues over the relevant range of alternative prices. Research for Penetration Pricing

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This is based on the concept that average unit of production costs continue to go down as cumulative output increases. Potential profits in the early stages of the product life cycle 26 are sacrificed in the expectation that higher volumes in later periods will generate sufficiently greater profits to result in overall profit for the product over its life. Following pricing pattern is adopted to increase market share: a. Offer a lower price (even below cost) when entering the market. b. Hold that price constant until unit costs produce a desired percentage markup. c. Reduce price as costs fail to maintain markup at the same desired percentage. Despite the ubiquitous nature of the above questions, researchers commonly encounter four limitations when using this approach for pricing research: I. it provides no competitive information. II. It relies on price awareness. III.it is inefficient when evaluating numerous product specifications. IV.it relies on aggregate-level analysis. Each limitation is discussed below. Provides no Competitive Information A concept test asks respondents to evaluate how likely they would be to purchase a specific product without any information about other products that might be available in the market. When shopping, consumers generally have the chance to see a set of competing products and pick one from the set. When presented with a set of products to select from, consumers can make tradeoffs between features and price to determine their preferred product. In the absence of this comparative task, respondents may have difficulty answering reliably. Relies on Price Awareness The respondent compares the price presented in the concept to an internal reference price to determine if the price is fair or not. This determination is based on a respondent‟s awareness of the current pricing in the category. Inefficient to Evaluate Various Product Specifications Often, a researcher would like to evaluate a small number of specific product variations at the same time price is being evaluated. For instance, there might be an interest in the market‟s willingness to pay for a specific feature or how the inclusion or exclusion of a product characteristic influences purchase likelihood. The concept test can be used to evaluate these various specifications. However, most researchers would suggest that each respondent only evaluate one concept. Therefore to evaluate various product specifications, the total sample size must grow. To illustrate, if we wished 200 observations per cell, and we are only testing three prices (three cells), we would require 600 respondents. However, if we have three alternative product variations, with each variation at three prices, we now have nine cells and would require 1800 respondents. Relies on aggregate-level analysis A concept test will rely on aggregate or at most subgroup-level analysis. That is, this approach will make respondent‟s heterogeneity difficult to detect and measure.

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The traditional concept test can be effectively used in pricing research when the product features are already determined, the level of price awareness is high, and the competitive 27 context is such that evaluating a single product is not too limiting. Distribution Research Traditionally, the distribution decisions in marketing strategy involve: · The number and location of salespersons, · Retail outlets, · Warehouses, and · The size of discount to be offered. The discount to be offered to the members in the channel of distribution usually is determined by what existing or similar products are offered, and also whether the firm wants to follow a “push” or a “pull” strategy. Warehouse and Retail Location Research Location decisions include: “What costs and delivery time would result, if we choose one location over another?” The approximate location (optimal location), that will minimize the distance to customers, weighted by the quantities purchased, will have to be determined. Chain shops with multiple outlets and franchise operations must decide on the physical location of their outlets. Data about surrounding residential neighborhood, income levels, and competitive stores would help in choosing optimal location. Number and location of Sales Representatives How many sales representatives should be there in a given territory? Approaches · Sales effort approach- when the product line is first introduced and there is no operating history to provide sales data. This is done by: ii. Estimating the number of sales calls required to sell to, and to service, prospective customers in an area for a year. This wills the sum of the number of visits required per year to each prospect (customer) in the territory. iii. Estimating the average number of sales calls per representative that can be made in that territory. iv. Divide the estimate in step (i) by the estimate in step (ii) to obtain the number of sales representatives required. · Statistical analysis approach- is used after the sales program is under way. Once a sales history is available from each territory, an analysis can be made to determine if the appropriate number of sales representatives is being used in each territory. An analysis of actual sales versus market potential for each sales representative can be made. Also, following inferences can be made: i. Average market potential is less as per each sales representative ii. Territory, which have too many sales representatives iii. Market potential is more but has too few sales representatives · Field Experiment approach- is also applicable only after the sales program has begun. Experiments are done with the calls made, to determine the number and location of sales representatives. This is done in two ways:

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i. Making more frequent calls on some prospects and less frequent calls on others, in order to see the effect on overall sales, keeping the number of sales representatives 28 unchanged. ii. Increasing the number of representatives in some territories and decreasing them in others to determine the sales effect. Promotion Research Here the focus is on the decisions that are commonly made when designing a promotion strategy. The decision for the promotion part of a market strategy can be divided into: · Advertising decisions, which have long-term effects. · Sales Promotion decisions, which affect the company in the short term. Companies spend more time and resources on advertising research than on sales promotion research because of the greater risk and uncertainty in advertising research. Advertising Research: Advertising decisions are more costly and risky. Advertising research involves generating information for making decisions in the: · Awareness stage · Recognition stage · Preference stage, and · Purchasing stage Most often, advertising research decisions are about advertising copy. Marketing research helps to determine how effective the advertisement will be. Research on media decisions is separate from advertising research. The effectiveness of an advertisement depends upon the brand involved and its advertising objectives. Four categories are used in advertising research: · Advertisement recognition · Recall of the commercial and its contents · The measure of commercial persuasion, and · The impact on the purchase behavior. Advertising Recognition The respondents are tested whether they can recognize the advertisement as one they have seen before.

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 CONCEPTS IN RESEARCH DESIGN Operational Definitions-is a definition stated in trace of specific testing criteria or 29 operations. Variable- this is used as a synonym for construct or the property being. Independent-A variable antecedents to dependent variable is called independent variable Dependent-If one variable depends upon or is a consequence of other variable, it is a dependent variable. Proposition-is a statement about concepts that may be judged as true or false if it refers to observable phenomenon. When a proposition is formulated for empirical testing it is called a hypothesis. The research hypothesis is a predictive statement that relatives an independent variable to deepens variable. Continuous Variablevariable which can assume any numerical value within a specific range.Value ever in decimal points e.g. age. Discrete Variable – A variable for which the individual values fall on the scale only no of children Independent Variable Dependent Variable Presumed cause presumed effect Stimulus Response Predicted from …….. Predicted to ……… Antecedent Consequence Manipulated Measured outcome Extraneous Variable- Some independent variables are not related to purpose of study, but may affect dependent variables is turned as extraneous variable. I.e. the researcher wants to test the hypothesis that there is a relationship between children‟s gains in social studies achievement and self their self concepts. Independent Variable-Self concept dependent variable – social studies echo intelligence may also effect social studies achievement since it is not related to purpose of studies, intravenous variable. Control -Minimize effect of extraneous independent variable. In experiment at researches, „control‟ is used to refer to restrain experimental conditions. Confounded Relationship-When the dependent variable is not free from influence of extraneous variables(s), the relation b/w independent variable and dependent variable is said to be confounded by an extraneous variable. Experimental and non-experimental hypothesis testing research: Research in which the independent variable is manipulated its turned „experimental hypothesis-testing‟ research and a research in which an independent variable is not manipulated is callednon–experimental hypotenuse-testing research. Experimental & Control Group: When a group is exposed to usual conditions, it is traced as „control gap‟ but when the gap is exposed to some moral or special condition, it is termed as „experimental gap‟.

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Treatment: the different conditions under which experimental and control gaps are put 30 are usually refereed to as „treatments‟. Different Research Design Different research designs can be conveniently described if we categorize them as: 1. Research design in case of exploratory research studies; 2. Research design in case of descriptive and diagnostic research studies, and 3. Research design in case of hypothesis-testing research studies. We take up each category separately 1: Research design in case of exploratory research studies: The major emphasis in such studies is on the discovery of ideas and insights. The research design appropriate for such studies must be flexible enough to provide opportunity for considering different aspects of a problem under study. Inbuilt flexibility in design is needed because the research problem, broadly defined initially, is transformed into one with more precise meaning in exploratory studies, which fact may necessitate changes in the research procedure for gathering relevant data. Generally, the following three methods in the context of research design for such studies are talked about: a. the survey of concerning literature; b. the experience survey and c. the analysis of „insight-stimulating‟. We let us discuss each of these methods a. Survey of concerning literature-This method happens to be the most simple and fruitful method of formulating precisely the research problem or developing hypothesis. Hypotheses stated by earlier works may be reviewed and their usefulness be evaluated as a basis for further research. He should also make an attempt to apply concepts and theories developed in different research contexts to the area in which he is himself working. Sometimes the works of creative writers also provide a fertile ground for hypothesis-formulation and as such may be looked into by the researcher. b. Experience survey means the survey of people who have had practical experience with the problem to be studied. The object of such a survey is to obtain insight into the relationships between variables and new ideas relating to the research problem. For such a survey people who are competent and can contribute new ideas may be carefully selected as respondents to ensure a representation of different types of experience. The investigator may then interview the respondents so selected. The researcher must prepare an interview schedule for the systematic questioning of informants. But the Interview must ensure flexibility in the sense that the respondents should be allowed to raise issues and questions that the investigator has not previously considered. c. Analysis of ‘insight-stimulating‟-It is also a fruitful method for suggest hypothesis for research. It is particularly suitable in areas where there is little experience to serve as a guide. This method consists of the intensive study of selected instances of the phenomenon in which one is interested. For this purpose the existing records, if any, may

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be examined, the unstructured interviewing may take place, or some other approach may be adopted. Attitude of the investigator, the intensity of the study and the ability of the 31 researcher to draw together diverse information into a unified interpretation are the main features, which make this method an appropriate procedure for evoking insights. Now, what sort of examples is to be selected and studied? Research design in case of descriptive and diagnostic research studies: Now another type of research studies are Descriptive research studies, those studies which are concerned with describing the characteristics of a particular individual, or of a group whereas diagnostic research studies determine the frequency with which something occurs or its association with something else. The studies concerning whether certain variables are associated are examples, diagnostic research studies, As against this, studies concerned with specific predication, with narration of facts and characteristics concerning individuals or group or situation are all examples of descriptive research studies. Most of the Group or Search Comes Under this Category The research design must make enough provision for protection against bias and must maximize reliability, with due concern for the economical completion of research study. The design in such studies must be rigid and not flexible and must focus attention on the following: a. Formulating the objective of the study b. Designing the methods of data collection c. Selecting the sample (how much material will be needed?) d. Collecting the data (where can the required data be found and with what time period should the data be related?) e. Processing and analyzing the data. f. Reporting the findings. Research design in case of hypothesis-testing research studies: Hypothesis-testing research studies (generally known as experimental studies) are those where the researcher tests the hypotheses of causal relationships between variables. Such studies require procedures that will not only reduce bias and increase reliability, but will permit drawing inferences about causality. Usually experiments meet this requirement. Hence, when we talk of research design in such studies, we often mean the design of experiments. Professor R.A. Fisher‟s name is associated with experimental designs. The study of experimental designs has its origin in agricultural research. Professor Fisher found that by dividing agricultural fields or plots into different blocks and then by conducting experiments in each of these blocks, whatever information is collected and inferences drawn from them, happens to be more reliable. This fact inspired him to develop certain experimental designs for testing hypotheses concerning scientific investigations. Today, the experimental designs are being used in research relating to phenomena of several disciplines. Now let us discuss the basic Principles of experimental designs. Basic Principles of Experimental Designs

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There are three principles of experimental designs: 32 1. Principle of Replication; 2. Principle of Randomization 3. Principle of Local Control Now let us discuss each one of these experimental design Principle of Replication In this design, the experiment should be repeated more than once. Thus, each treatment is applied in many experimental units instead of one. By doing so the statistical accuracy of the experiments is increased. For example, suppose we are to examine the effect of two varieties of rice. For this purpose we may divide the field into two parts and grow one variety in one part and the other variety in the other part. We can then compare the yield of the two parts and draw conclusion on that basis. But if we are to apply the principle of replication to this experiment, then we first divide the field into several parts, grow one variety in half of these parts and the other variety in the remaining parts. We can then collect the data of yield of the two varieties and draw conclusion by comparing the same. The result so obtained will be more reliable in comparison to the conclusion we draw without applying the principle of replication. Principle of Randomization This principle indicates that we should design or plan the experiment in such a way that the variations caused by extraneous factor can all be combined under the general heading of “chance.” For example - if grow one variety of rice, say, in the first half of the parts of a field and the other variety is grown in the other half, then it is just possible that the soil fertility may be different in the first half in comparison to the other half. If this is so our results would not be realistic. In such a situation, we may assign the variety of rice to be grown in different parts of the field on the basis of some variety „sampling technique, i.e., we may apply randomization principle and random ourselves against the effects of the extraneous factors (soil fertility processes in the given case. The Principle of Local Control is another important principle of experimental designs. Under it the extraneous factor, the known source of variability, is made to vary deliberately over as wide a range as necessary and this needs to be done in such a way that the variability it causes can be measured and hence eliminated from the experimental error. This means that we should plan the experiment in a manner that we can perform a twoway analysis of variance, in which the total variability of the data is divided into three components attributed to treatments (varieties of rice in our case), the extraneous factor (soil fertility in our case) and experimental error. In other words, according to the principle of local control, we first divide the field into several homogeneous parts, known as blocks, and then each such block is divided into parts equal to the number of treatments. Then the treatments are randomly assigned to these parts of a block. Important Experimental Designs

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Experimental design refers to the framework or structure of an experiment and such there are several experimental designs. We can classify experimental designs into two broad 33 categories. informal experimental designs and formal experimental designs. Informal experimental designs are designs that normally use a less sophisticated form of analysis based on differences in magnitudes, whereas formal experimental designs offer relatively more control and use precise statistical procedures for analysis. Important experimental designs are as follows: a. Informal experimental designs: I. Before-and-after without control design. II. After-only with control design. III. Before-and-after with control design. B.Formal experimental designs: i. Completely randomized design (C. R. design) ii. Randomized block design (R. B. design) iii. Latin square design (L.S. design). iv. Factorial designs. We may briefly discuss with each of the above stated informal as well as formal experimental designs. i. Before-and-after without Control Design: In such a design a single test group or area is selected and the dependent variable is measured before the introduction of the treatment The treatment is then introduced and the dependent variable is measured again after the treatment has been introduced. The effect of the treatment would be equal to the level - of the phenomenon after the treatment minus the level of the phenomenon before the treatment. The design can be represented thus: The main difficulty of such a design is that with the passage of time considerable extraneous variations may be there in its treatment effect. ii. After-only with Control Design: This can be exhibited in the following form: The basic assumption in such a design is that the two areas are identical with respect to their behavior towards the phenomenon considered. If this assumption is not true, there is the possibility of extraneous variation entering into the treatment effect. However, data can be collected in such a design without the introduction of problems with the passage of time. In this respect this design is superior to before-and-after without control design. iii. Before-and-after with control design: In this design two areas are selected and the dependent- variable is measured in both the areas for an identical time-period before the treatment. The treatment is then introduced into the test area only, and the dependent variable is measured in both for an identical time-period after the introduction of the treatment The treatment effect is determined by subtracting the change in the dependent variable in the control area from the change in the dependent variable in test area. This design can be shown in this way:

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This design is superior to the above two designs for the simple reason that it avoids extraneous variation resulting both from the passage of time and from non-comparability 34 of the test and control areas. But at times, due to lack of historical data, time or a comparable control area, we should prefer to select one of the first two informal designs stated above. iv. Completely randomized design (C.R. design) – It involves only two principles viz., the principle of replication and the principle of randomization of experimental designs. It is the simplest possible design and its procedure of analysis is also easier. The essential characteristic of this design is that subjects are randomly assigned to experimental treatments (or vice-versa). For Example - If we have 10 subjects and if we wish to test 5 under treatment A and 5 under treatment B, the randomization process gives every possible group of 5 subjects selected from a set of 10 an equal opportunity of being assigned to treatment A and treatment B. One-way analysis of variance (or one-way ANOVA) is used to analyse such a design. Such a design is generally used when experimental areas happen to be homogeneous. Technically, when all the variations due to uncontrolled extraneous factors are included under the heading of chance variation, we refer to the design of experiment as C. R. design. We can present a brief description of the two forms of such a design is given below.

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 THE QUESTIONNAIRE-PROS AND CONS 35 The advantages of administering a questionnaire instead of conducting an interview are: The primary advantages of questionnaire are i. it is economical in terms of money and time ii. it gives samples which are more representative of population iii. it generates the standardized information iv. it provides the respondent the desired privacy We will discuss these advantages of Questionnaire technique of collecting primary data 1. Economical in Money and Time The questionnaires will save your time and money. the time of operation and is economical. collected simultaneously, however when personal interview is done the interviewer has to go to each and every individual separately. respondents very efficiently. Finally, the cost of postage should be less than that of travel or telephone expenses. Recent developments in the science of surveying have led to incorporating computers into the interview process, yielding what is commonly known as computer automated telephone interview (or CATI) surveys. Advances in using this survey technique have dramatically reshaped our traditional views on the time-intensive nature and inherent unreliability of the interview technique. 2. Better Samples Many surveys are constrained by a limited budget. Since a typical questionnaire usually has a lower cost per respondent, you can send it to more people within a given budget (or time) limit. This will provide you with more representative samples. 3. Standardization The questionnaire provides you with a standardized data-gathering procedure. alter the pattern of question asking, calling at inconvenient times, and biasing by “explaining”) can be minimized by using a well-constructed questionnaire. introduced by the feelings of the respondents towards the interviewer (or vice versa). 4. Respondent Privacy debatable; most surveyors believe the respondent will answer a questionnaire more frankly than he would answer an interviewer, because of a greater feeling of anonymity. and need have no fear of anyone hearing them. To maximize this feeling of privacy, it is important to guard, and emphasize, the respondent‟s privacy The primary disadvantages of the questionnaire are discussed on the grounds of: i. non return ii. Mis-interpretation

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iii. Validity 36 We will discuss them in detail. 1. Non Returns Non returns are questionnaires or individual questions that are not answered by the people to whom they were sent. For example, you may be surveying to determine the attitude of a group about a new policy. Some of those opposed to it might be afraid to speak out, and they might comprise the majority of the non returns. This would introduce non-random (or systematic) bias into your survey results, especially if you found only a small number of the returns were in favors of the policy. Non returns cannot be overcome entirely. What we can do is try to minimize them. Techniques to accomplish this we will be studying later on. 2. Misinterpretation Misinterpretation occurs when the respondent does not understand either the survey instructions or the survey questions. If respondents become confused, they will either give up on the survey (becoming a no return) or answer questions in terms of the way they understand it, but not necessarily the way you meant it. This would turn out to be more serious than non return , sometimes. Your questionnaire‟s instructions and questions must be able to stand on their own and you must use terms that have commonly understood meanings throughout the population under study. If you are using novel terms, be sure to define them so all respondents understand your meaning. 3. Validity The third disadvantage of using a questionnaire is inability to check on the validity of the answer. Without observing the respondent‟s reactions (as would be the case with an interview) while completing the questionnaire, You have no way of knowing the true answers to following questions to a friend or complete it personally? nt deliberately choose answers to mislead the surveyor? Cover Letter The cover letter should explain to the respondent the purpose of the survey and it should motivate him to reply truthfully and quickly. explain why the survey is important to him, how he was chosen to participate, and who is sponsoring the survey (the higher the level of sponsorship the better). confidentiality of the results , it will help in minimizing both no return and validity problems. · Keep the language simple.

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Analyze your audience and write on their level. Avoid the use of technical terms. An appropriate corollary to Murphy‟s Law in this case would be: “ If someone can 37 misunderstand something, they will”. · Keep the questions short. Long questions tend to become ambiguous and confusing. A respondent, in trying to comprehend a long question, may leave out a clause and thus change the meaning of the question. · Keep the number of questions to a minimum. There is no commonly agreed on maximum number of questions that should be asked, but research suggests higher return rates correlate highly with shorter surveys. Ask only questions that will contribute to your survey. Apply the “So what?” and “Who cares?” tests to each question. “Nice-to-know” questions only add to the size of the questionnaire. having said this, keep in mind that you should not leave out questions that would yield necessary data simply because it will shorten your survey. If the information is necessary, ask the question. · Limit each question to one idea or concept. A question consisting of more than one idea may confuse the respondent and lead to a meaningless answer. Consider this question: “Are you in favors of raising pay and lowering benefits?” What would a yes (or no) answer mean? · Do not ask leading questions. These questions are worded in a manner that suggests an answer. Some respondents may give the answer you are looking for whether or not they think it is right. Such questions can alienate the respondent and may open your questionnaire to criticism. A properly worded question gives no clue as to which answer you may believe to be the correct one. Use subjective terms such as good, fair, and bad sparingly, if at all. These terms mean different things to different people. One person‟s “fair” may be another person‟s “bad.” How much is “often” and how little is “seldom?” · Allow for all possible answers. Respondents who cannot find their answer among your list will be forced to give an invalid reply or, possibly, become frustrated and refuse to complete the survey. Wording the question to reduce the number of possible answers is the first step. Avoid dichotomous (two-answer) questions (except for obvious demographic questions such as gender). If you cannot avoid them, add a third option, such as no opinion, don‟t know, or other. These may not get the answers you need but they will minimize the number of invalid responses. A great number of “don‟t know” answers to a question in a fact-finding survey can be a useful piece of information. But a majority of other answers may mean you have a poor question, and perhaps should be cautious when analyzing the results. · Avoid emotional or morally charged questions. The respondent may feel your survey is getting a bit too personal!

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· Understand the should-would question. Respondents answer “should” questions from a social or moral point of view while answering “would” questions in terms of personal 38 preference. · Formulate your questions and answers to obtain exact information and to minimize confusion. For example, does “How old are you?” mean on your last or your nearest birthday? By including instructions like “Answer all questions as of (a certain date)”, you can alleviate many such conflicts. · Include a few questions that can serve as checks on the accuracy and consistency of the answers as a whole. Have some questions that are worded differently, but are soliciting the same information, in different parts of the questionnaire. These questions should be designed to identify the respondents who are just marking answers randomly or who are trying to game the survey (giving answers they think you want to hear). If you find a respondent who answers these questions differently, you have reason to doubt the validity of their entire set of responses. For this reason, you may decide to exclude their response sheet(s) from the analysis. · Organize the pattern of the questions: Place demographic questions at the end of the questionnaire. · Have your opening questions arouse interest. · Ask easier questions first. · To minimize conditioning, have general questions precede specific ones. Group similar questions together. · If you must use personal or emotional questions, place them at the end of the questionnaire. Pretest (Pilot test) the Questionnaire This is the most important step in preparing your questionnaire. The purpose of the pretest is to see just how well your cover letter motivates your respondents and how clear your instructions, questions, and answers are.  You should choose a small group of people (from three to ten should be sufficient) you feel are representative of the group you plan to survey.  After explaining the purpose of the pretest, let them read and answer the questions without interruption.  When they are through, ask them to critique the cover letter, instructions, and each of the questions and answers. Don‟t be satisfied with learning only what confused or alienated them. Question them to make sure that what they thought something meant was really what you intended it to mean.  Use the above 12 hints as a checklist, and go through them with your pilot test group to get their reactions on how well the questionnaire satisfies these points.  Finally, redo any parts of the questionnaire that are weak.

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Have your questionnaire neatly produced on quality paper. A professional looking product will increase your return rate. A poorly designed survey that contains poorly 39 written questions will yield useless data regardless of how “pretty” it looks. Finally, make your survey interesting Let us now summaries what we have studied today.  The questionnaire is the means for collecting your survey data.  It should be designed with your data collection plan in mind.  Each of its three parts the cover letter, instructions and questions should take advantage of the strengths of questionnaires while minimizing their weaknesses.  Each of the different kinds of questions is useful for eliciting different types of data, but each should be constructed carefully with well- developed construction guidelines in mind.  Properly constructed questions and well-followed survey procedures will allow you to obtain the data needed to check your hypothesis and, at the same time, minimize the chance that one of the many types of bias will invalidate your survey results. The types of bias which you will be encounter with when you prepare and execute a questionnaire with be studied in the next lecture. Levels of Measurement from lowest to highest, are as follows: · Nominal · Ordinal · Interval · Ratio Types of Measurement Scales Ordinal and nominal data are always discrete. Continuous data has to be at either ratio or interval level of measure now let us discusses these in detail: Nominal Level of Measurement Nominal variables include demographic characteristics like sex, race, and religion. The nominal level of measurement describes variables that are categorical in nature. The characteristics of the data you‟re collecting fall into distinct categories: · If there are a limited number of distinct categories (usually only two), then you‟re dealing with a dichotomous variable. · If there are an unlimited or infinite number of distinct categories, then you‟re dealing with a continuous variable. Ordinal Level of Measurement · The ordinal level of measurement describes variables that can be ordered or ranked in some order of importance. · It describes most judgments about things, such as big or little, strong or weak. · o Most opinion and attitude scales or indexes in the social sciences are ordinal in nature Interval Level of Measurement The interval level of measurement describes variables that have more or less equal intervals, or meaningful distances between their ranks. For example, if you were to ask

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somebody if they were first, second, or third generation immigrant, the assumption is that 40 the distance or number of years, between each generation is the same.  Ratio Level of Measurement The ratio level of measurement describes variables that have equal intervals and a fixed zero (or reference) point. It is possible to have zero income, zero education, and no involvement in crime, but rarely do we see ratio level variables in social science since it‟s almost impossible to have zero attitudes on things, although “not at all”, “often”, and “twice as often” might qualify as ratio level measurement. Advanced statistics require · At least interval level measurement, so the researcher always strives for this level, · Accepting ordinal level (which is the most common) only when they have to. · Variables should be conceptually and operationally defined with levels of measurement in mind since it‟s going to affect the analysis of data later Reliability and Validity For a research study to be accurate, its findings must be both reliable and valid.  Reliability Research means that the findings would be consistently the same if the study were done over again Validity A valid measure is one that provides the information that it was intended to provide. The purpose of a thermometer, for example, is to provide information on the temperature, and if it works correctly, it is a valid thermometer. There are many different types of longitudinal research, such as those that involve timeseries (such as tracking a third world nation‟s economic development over four years or so). The general rule is to use longitudinal research the greater the number of variables you‟ve got operating in your study and the more confident you want to be about cause and effect. Methods of Measuring Reliability Now, the question arises that how will you measure the reliability of a particular measure? There are four good methods of measuring reliability: · Test-retest · Multiple forms · Inter-rater · Split-half · Test-retest  Test-retest The Test Retest in the same group technique is to administer your test, instrument, survey, or measure to the same group of people at different points in time. Most researchers administer what is called a pretest for this, and to troubleshoot bugs at the same time. All reliability estimates are usually in the form of a correlation coefficient, so here, all you do is calculate the correlation coefficient between the two scores of each group and report it as your reliability coefficient. Multiple Forms

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The multiple forms technique has other names, such as parallel forms and disguised testretest, but it‟s simply the scrambling or mixing up of questions on your survey, for 41 example, giving it to the same group twice. It‟s a more rigorous test of reliability. Inter-rater Inter-rater reliability is most appropriate when you use assistants to do interviewing or content analysis for you. To calculate this kind of reliability, all you do is report the percentage of agreement on the same subject between your raters, or assistants. Split-half Taking half of your test, instrument, or survey, and analyzing that half as if it were the whole thing estimate split-half reliability. Then, you compare the results of this analysis with your overall analysis. Methods of Measuring Validity Once you find that your measurement of variable under study is reliable, you will want to measure its validity. There are four good methods of estimating validity: · Face · Content · Criterion · Construct  Face Validity Face validity is the least statistical estimate (validity overall is not as easily quantified as reliability) as it‟s simply an assertion on the researcher‟s part claiming that they‟ve reasonably measured what they intended to measure. It‟s essentially a “take my word for it” kind of validity. Usually, a researcher asks a colleague or expert in the field to vouch for the items measuring what they were intended to measure. Content Validity Content validity goes back to the ideas of conceptualization and operation allegation. If the researcher has focused in too closely on only one type or narrow dimension of a construct or concept, then it‟s conceivable that other indicators were overlooked. In such a case, the study lacks content validity Content validity is making sure you‟ve covered all the conceptual space. There are different ways to estimate it, but one of the most common is a reliability approach where you correlate scores on one domain or dimension of a concept on your pretest with scores on that domain or dimension with the actual test. Another way is to simply look over your inter-item correlations. Criterion Validity Criterion validity is using some standard or benchmark that is known to be a good indicator. There are different forms of criterion validity: · Concurrent validity is how well something estimates actual day-by-day behavior; · Predictive validity is how well something estimates some future event or manifestation that hasn‟t happened yet. It is commonly found in criminology. Construct Validity Construct validity is the extent to which your items are tapping into the underlying theory or model of behavior. It‟s how well the items hang together (convergent validity) or

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distinguish different people on certain traits or behaviors (discriminant validity). It‟s the most difficult validity to achieve. You have to either do years and years of research or 42 find a group of people to test that have the exact opposite traits or behaviors you‟re interested in measuring. Attitude Measurement Many of the questions in a questionnaire are designed to measure attitudes. Attitudes are a person‟s general evaluation of something. Customer attitude is an important factor for the following reasons: · Attitude helps to explain how ready one is to do something. · Attitudes do not change much over time · Attitudes produce consistency in behavior. · Attitudes can be related to preferences. Attitudes can be measured using the following procedures: · Self-reporting - subjects are asked directly about their attitudes. Self-reporting is the most common technique used to measure attitude. · Observation of behavior - assuming that one‟s behavior is a result of one‟s attitudes, attitudes can be inferred by observing behavior. For example, one‟s attitude about an issue can be inferred by whether he/she signs a petition related to it.  Response Methods Questioning is a widely used stimulus for measuring concepts. A manager may be asked his or her views concerning an employee. The response is,” a good machinist,” “a troublemaker,” “a union activist,” “reliable,” or “a fast worker with a poor record of attendance.” These answers represent different frames of reference for evaluating the worker and are often of limited value to the researcher. Two approaches improve the usefulness of such replies. First, various properties may be separated arid the respondent asked to judge each specific facet. Here, several questions are substituted for structuring devices. To quantify dimensions that are essentially qualitative, rating scales or ranking scales are used. Rating Scales One uses rating scales to judge properties of objects without reference to other similar objects. These ratings may be in such forms as “like-dislike,” “approve-indifferent disapprove,” or other classifications using even more categories. There is little conclusive support for choosing a three-point scale over scales with five or more points. Some researchers think that more points on a rating scale provide an opportunity for greater sensitivity of measurement and extraction of variance. The most widely used scales range from three to seven points, but it does not seem to make much difference which number is used-with two exceptions.4 First, a larger number of scale points is needed to produce accuracy with single-item versus multiple-item scales. Second, in cross-cultural measurement, the culture may condition respondents to a standard metric-a ten-point scale in Italy. Ranking Scales

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 In ranking scales, the subject directly compares two or more objects and makes choices among them. Frequently, the respondent is asked to select one as the 43 “best” or the “most preferred.” When there are only two choices, this approach is satisfactory, but it often results in “ties” when more than two choices are found. For example, respondents are asked to select the most preferred among three or more models of a product. Assume that 40 percent choose model A, 30 percent choose model B. and 30 percent choose model C.  Which is the preferred model?” The analyst would be taking a risk to suggest that A is most preferred. Perhaps that interpretation is correct, but 60 percent of the respondents chose some model other than A.  Perhaps all B and C voters would place  A last, preferring either B or C to it. This ambiguity can be avoided by using some of the techniques described in this section. Some of the measurement scales are discussed below:  Equal-appearing Interval Scaling In this scale a set of statements are assembled. These statements are selected according to their position on an interval scale of favorableness. Statements are chosen that has a small degree of dispersion. Respondents then are asked to indicate with which statements they agree. Likert Method of Summated Ratings In this scale a statement is made and the respondents indicate their degree of agreement or disagreement on a five-point scale (Strongly Disagree, Disagree, neither Agree nor Disagree, Agree,Strongly Agree). It actually extends beyond the simple ordinal choices of “strongly agree”, “agree”, “disagree”, and “strongly disagree” In fact, Likert scaling is initially assigned through a process that calculates the average index score for each item in an index and subsequently ranks them in order of intensity (recall the process for constructing Turnstone scales). Once ordinality has been assigned, the assumption is that a respondent choosing a response weighted with say 15 out of 20 in an increasing scale of intensity is placed at that level for the index. Example of a Likert Scale How would you rate the following aspects of your food store? Extremely Important unimportant Service 1 2 3 4 5 6 7 Check outs 1 2 3 4 5 6 7 Bakery 1 2 3 4 5 6 7 Deli 1 2 3 4 5 6 7 Semantic Differential scale A semantic differential scale is constructed using phrases describing attributes of the product to anchor each end. For example, the left end may state, “Hours are inconvenient” and the right end may state, “Hours are convenient”. The respondent then marks one of the seven blanks between the statements to indicate his/her opinion about the attribute.

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 SAMPLING Sampling is the selection of part of an aggregate or totality known as population, on the 44 basis of which a decision concerning the population is made. Thus, we can say that a finite subset of statistical individuals in a population is called a sample and the number of individuals in a sample is called sample size. Sampling Unit A unit is a person, animal, plant or thing which is actually studied by a researcher; the basic objects upon which the study or experiment is executed.For example, a person; a sample of soil; a pot of seedlings; a zip code area; a doctor‟s practice. Activity Define population and sampling unit in each of the following problems 1. Popularity of family planning among families having more than two children _____________ 2. Election for a political office with adult franchise__________ 3. Measurement of the volume of timber available in a forest _______________________ 4. Annual yield of apple fruit in a hilly district.______ 5. Study of child mortality rate in a district Parameter and Statistic A parameter is an unknown value, and therefore it has to be estimated. Parameters are used to represent a certain population characteristic. For example, the population means m is a parameter that is often used to indicate the average value of a quantity. Within a population, a parameter is a fixed value that does not vary. Each sample drawn from the population has its own value of any statistic that is used to estimate this parameter. For example, the mean of the data in a sample is used to give information about the overall mean min the population from which that sample was drawn. A statistic is a quantity that is calculated from a sample of data. It is used to give information about unknown values in the corresponding population. For example, the average of the data in a sample is used to give information about the overall average in the population from which that sample was drawn. Variables A characteristic or phenomenon, which may take different, values, such as weight, gender since they are different from individual to individual. Any object or event, which can vary in successive observations either in quantity or quality, is called a “variable.”Variables are classified accordingly as quantitative or qualitative. A qualitative variable does not vary in magnitude in successive observations. The values of quantitative called “Attributes”. A quantitative variable does vary in magnitude in successive observations. The values of quantitative are called “Varieties” Variable Randomness Randomness means unpredictability

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The fascinating fact about inferential statistics is that, although each random observation may not be predictable when taken alone, collectively they follow a predictable pattern 45 called its distribution function. For example, it is a fact that the distribution of a sample average follows a normal distribution for sample size over 30. In other words, an extreme value of the sample mean is less likely than an extreme value of a few raw data. Desirable Characteristics of Sample Statistics 1. Unbiased: If the arithmetic mean of the statistic calculated for all possible samples of a given size n exactly equals its population parameter. 2. Sufficient: Summarizes all relevant information about the parent population contained in the sample, while ignoring any sample specific information. 3. Efficient: The more the statistic values for various samples cluster around the true parameter value, the lower the sampling error and the greater the efficiency. Consider an archer shooting at a target. The archer wants to be accurate, but also wants the arrows to cluster as closely to the centre of the target as possible. 4. Consistent: The larger the sample size, the closer the statistic should be to its parameter value. Every statistic in a sample might have a different sampling distribution Sampling Distribution The sampling distribution is a hypothetical device that figuratively represents the distribution of a statistic (some number you‟ve obtained from your sample) across an infinite number of samples. That‟s because the center of the sampling distribution represents the best estimate of the population average, and the population is what you want to make inferences to. The average of the sampling distribution is the population parameter, and inference is all about making generalizations from statistics (sample) to parameters (population). Relation between Standard Error and Sample Size Standard error is also related to sample size.The larger your sample, the smaller the standard error. You‟re not reducing bias or anything by increasing sample size, only coming closer to the total number in the population. Validity and sampling error are somewhat similar. However, you can estimate population parameters from even small samples. Principles of Sample Survey The theory of sampling is based on the following important principles: 1. Principle of statistical regularity 2. Principle of validity 3. Principle of optimization 1. Principle of statistical regularity Stresses the desirability and importance of selecting a sample at random so that each and every unit in the population has an equal chance of being selected in the sample. We get an immediate derivation from this principle is the principle of Inertia of large numbers which states that “Other things being equal as the sample size increases, the results tend to be more reliable and accurate.” For example, in a coin tossing experiment, the results will be

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approximately 50% heads and 50% tails provided we perform the experiment a fairly 46 large number of times. 2. Principle of validity means the sample design should enable us to obtain valid tests and estimates about the parameters of the population. The samples obtained by the technique of probability sampling satisfy this principle. 3. Principle of optimization impresses upon obtaining optimum results in terms of efficiency and cost of the design with the resources at disposal. The reciprocal of the sampling variance of an estimate provides a measure of its efficiency while a measure of cost of the design is provided by the total expenses incurred in terms of money and man hour. The principle of optimization consists in a. achieving a given level of efficiency at minimum cost b. obtaining maximum possible efficiency with given level of cost. Sampling and Non-sampling Error We can classify broadly the errors involved in the process of research into two heads: Sampling Errors and Non-Sampling Errors Sampling Errors These have the origin in sampling and arise out of the fact that only a part of the population is used to estimate the population parameters and draw inferences about the population. Therefore, sampling errors are absent in complete enumeration. The sampling errors are basically because of following reasons: a. Faulty selection of sample: If you use a defective technique for selecting a sample, e.g purposive or judgment sampling in which the investigator deliberately chooses the sample in order to deduce the desired results. This bias can be overcome by adhering to Simple Random Sampling. b.Substitution: If you substitute one unit for another if some difficulty arises in studying that particular unit (first one), this leads to some bias. This is because of the fact that the characteristics possessed by the substituted unit will usually be different from those possessed by the unit originally included in the sample. c . Faulty Demarcation of sampling units It is significant in particularly areas surveys such as agricultural experiments in the field or in the crop cutting fields etc. d. Constant error due to improper choice of the statistics for estimating the population parameters: For example while estimating the standard deviation of population if we divide the sum of squares by “n” instead of “n-1”,we get an unbiased estimate of population standard deviation.  Non-sampling Errors The non -sampling errors primarily arise at the stages of · Observation · Ascertainment

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· Processing of data These are, therefore present in both complete enumeration and sample survey. Non- 47 sampling errors can occur at every stage of planning or execution of census or sample survey. It is very difficult to prepare an exhaustive list of the sources of non-sampling errors. However some of the more important ones arise because of following factors: 1. Faulty planning or definition. 2. Response Errors 3. Non- Response bias 4. Errors in coverage 5. Compiling Errors 6. Publication Errors  Now we will discuss them in detail 1. Faulty planning or Definition: As we all know the foremost step in research is explicitly stating the objectives of the study. These objectives are then translated into · A set of definitions of the characteristics for which data is to be collected · Into a set of specifications for collection, processing and publishing. Here Non-Sampling Errors may Arise Due to a. Data specification being inadequate and inconsistent with respect of the objectives of study b. Error due to location of the units and actual measurement of the characteristics, errors in recording the measurements, errors due to ill designed questionnaires. c. Lack of trained and qualified investigators and 2. Response Errors There arise as a result of the responses furnished by the respondents because of following reasons · Response error may be accidental- e.g, the respondent may understand a particular question and accordingly furnish improper information un-intentionally. · Prestige Bias · Self-Interest · Bias due to interviewer · Failure of respondent‟s memory 3. Non- Response Bias Non-Response biases occur if you do not obtain full information from all the sampling units. 4. Errors in Coverage If the objectives are not stated concisely in a clear cut manner it may lead to · Certain units which should not be included also gets included · Certain units which must be included gets excluded 5. Compiling Errors

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Various operations of data processing such as editing and coding of the responses, punching of cards, tabulation and summarizing the original observations made in study 48 are the potential source of error. Compilation errors are subject to control through verification, consistency check, etc. 6. Publication Errors The errors committed during presentation and printing of tabulated results is basically due to two sources: · Mechanics of publication-the proofing error and the like. · Failure of the survey organization to point out the limitations of the statistics. Advantages of sampling over complete enumeration The following are the advantages and/or necessities for sampling in statistical decisionmaking: 1. Cost: Cost is one of the main arguments in favors of sampling, because often a sample can furnish data of sufficient accuracy and at much lower cost than a census. 2. Accuracy: Much better control over data collection errors is possible with sampling than with a census, because a sample is a smaller-scale undertaking. 3. Timeliness: Another advantage of a sample over a census is that the sample produces information faster. This is important for timely decision making. 4. Amount of Information: More detailed information can be obtained from a sample survey than from a census, because it take less time, is less costly, and allows us to take more care in the data processing stage. 5. Destructive Tests: When a test involves the destruction of an item under study, sampling must be used. Statistical sampling determination can be used to find the optimal sample size within an acceptable cost. Limitations of Sampling The advantages of sampling over complete enumeration can be derived only if · The sampling units are drawn in a scientific manner, · The appropriate sampling technique is used, and · The sample size is adequate Sampling theory has its own limitations and problems which may be briefly outlined as 1. You have to take proper care in the planning and execution of the sample survey, otherwise the results obtained might be inaccurate and misleading 2. Until and unless sampling is done by trained and efficient personnel and sophisticated equipment for its planning, execution and analysis. In absence of these sampling is not trustworthy 3. If you want to have information of each and every unit of population you will have to go for complete enumeration only. In that case sampling will not be an appropriate method. Types of Sampling

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The type of enquiry and the nature of data fundamentally determine the technique or method of selecting a sample .The procedure of selecting a sample may be broadly 49 classified under the following three heads: · Non-Probability Sampling Methods: Subjective or Judgment Sampling · Probability Sampling · Mixed Sampling These we will be studying in detail in the next lecture. Now, briefly tell me what concepts you have studied today? Yes, we studied various concepts like population, statistic, variables qualitative and quantitative, variable randomness, characteristics of sample statistic, sampling distribution, standard error, principles of sample survey , sampling and non-sampling errors, merits and limitations of sampling. This topic also prepare urself
Data analysis – Univariate analysis – Bivariate analysis – Multivariate analysis Simple and cross tabulation, simple and multiple regression, Factor analysis Hypothesis testing – Types of tests and test selection, One sample test, TwoIndependent Sample tests, Two-related sample tests. Chi-square test, tests for large and small samples. (Numericals expected)

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 STEPS OF REPORT WRITING Information Reports They are the first step to understanding the existing situation (for instance-business, economic, technological, labour market or research scenario) or what has been discussed or decided (minutes of a meeting). They, you should remember, form the foundation of subsequent decision reports and research reports. In describing any person, object, situation or concept, the following seven questions will help you to convey a comprehensive picture Subject /Object Who? Or whom? Where? How? Action Reason What? When? Why?

Therefore, you can check the comprehensiveness of an information or descriptive report by iteratively asking: Who Does What to Whom? When, Where, How and WHY?  Steps of Report Writing Preparing the Draft Preparation of reports is time consuming and expensive. Therefore, you, while writing your report should ensure that they are very sharply focused in purpose, content and readership. To control the final outcome of your product – whether it is a research report, committee/consulting/administrative report or a student report – I advise that you precede it with a proposal/draft and its acceptance or modification and periodic interim reports and their acceptance or modification by your sponsor. Your proposal should provide information on the following items: · Descriptive title of your study · Your name as the author and your background · Nature of your Study · Problem to be examined · Need for the study · Background information available · Scope of study · To whom will it be useful? · Hypothesis, if any, to be tested · Data · Sources · Collection procedure

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· Methodology for analysis 51 · Equipment and facilities required · Schedule-target dates for completing · Library research · Primary research · Data analysis · Outline of the report · First draft · Final draft · Likely product or tentative outline · Bibliography Reviewing the Draft To err is human. Therefore after you have prepared your draft report, it should be thoroughly reviewed and edited before the final report is submitted. Let us now try to make a checklist that will help you in reviewing the draft · Your purpose as the author? · Reader‟s profile? · Content? · Language and tone? · Length? · Appearance? Author’s Purpose The lack of clarity and explicitness in the communication process leads to two major problems · Confusion in determining the mix of content, language and tone · Misinterpretation of the message Therefore try to use a simple, easy to read style and presentation that will help your reader to understand the content easily. Reader’s Profile Readership may consist of one or more person(s) / group(s). You would therefore need to check whether all of them have the same wavelength. If not, common interest areas will need to be segregated from the special interest areas. Then you will need to decide on the types and parts of the report that can satisfy the various reader groups. The major discriminating features of the readers profile are culture, religion, ideologies, age, education and economic background Content Please pay attention to the content‟s focus, its organization, and accuracy of facts and logic of arguments. · You should clarify the focus right in the first few paragraphs to attract the reader‟s attention and hold it. · If any material is added or deleted in the text, recheck the focus to see whether you need to make any changes in the foundation

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· Keep in mind that you may loose credibility if you fail to check for the accuracy of the facts, for a reader can easily test internal consistency of the report by comparing 52 information across pages and sections · Not all the data that is required to make the report may be available. Sometimes you may need to make assumptions to fill the gaps · What is good in one situation may not hold for another. Therefore please list and arrange the elements and the actors of a situation to understand its dynamics Language and Tone Since the purpose of communication is to make the reader understand the message, use vocabulary and sentence structure which the reader understands. Abstract phrases are difficult to comprehend while concrete phrases are easy to understand. Finally, the tone of the language also matters. It can make the reader receive, ignore or reject the message. Length This is a matter that needs to be judged by you as the author keeping in mind the purpose, subject and the reader‟s interest. Usually, shorter the content, the more attractive it is to the reader. However it should not be so brief as to miss the essential points and linkages in the flow of arguments and force the reader to ask for more information. Let us now try to work on a few tips to save words. Can you think of any? · Cut out repetitions, unless they are needed to sharpen the Message · Take out redundancies · Use active voice · Use shorter and direct verbs You have done quite a good job of this. Can you also give me some examples for the above? Hey! That‟s nice. You‟ve covered most of the tips. I‟ll just add a few more to complete the list. · Eliminate weighty expressions · Make concrete adjectives · Use abbreviations which are more familiar than their expanded form Appearance Looks Matter! Don‟t you all agree with this? This therefore also holds true for your report. The novelty of presentation is as important as the originality of ideas. Both are products of creativity. Presentation attracts readers and content holds their attention. Hence pay complete attention to both the product and its packaging. Proof Reading If you or another person proofreading your report is good, he should have the accuracy to pin point all the mistakes, clarity in giving instructions to the printer and speed for meeting the printer‟s deadline. · Make sure that you indicate correction marks at two places

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· Within the line where the correction is to be carried out 53 · In the margin against the corresponding line giving the instruction · Please, never give instructions at the place of correction · You should mark the proof preferably with a red ball point · To catch as many errors as possible read it over and over again · One last point. Always remember that proofs are meant to be corrected not edited Final Printing Phew! At last your job is almost over. Once you have thoroughly proof read your report, you should: · Return it to the printer according to the agreed schedule · Also return the manuscript along with · Upon printing, your final document is ready for reference Format of a Report: No matter which category your report falls into, when you make one, make sure that it contains each of the following parts · A cover and title page · Introductory Pages · Foreword · Preface · Acknowledgement · Table of Contents · List of tables and illustrations · Summary · Text · Headings · Quotations · Footnotes · Exhibits · Reference Section · Appendices · Bibliography · Glossary (if required) We will now discuss each of these at length · Cover and the title page I am sure you would all know what details this page needs to contain. However, let‟s try to list them down again · Title of the subject or project · Presented to whom · On what date · For what purpose · Written by whom If there is any restriction on the circulation of the report that you have made, you should indicate it on the top right corner of the cover and title page

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Sample For official use only Working capital requirements Of Xyz private limited Presented to Managing director Xyz private limited On November 26, 2003 By Ms. ABC And Ms. DEF Style is the way you communicate

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