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Published on May 2016 | Categories: Types, School Work, Homework | Downloads: 70 | Comments: 0 | Views: 1568
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T-TEST PRACTICE PROBLEM
A researcher hypothesizes that electrical stimulation of the lateral habenula will result in a decrease in food intake (in this case, chocolate chips) in rats. Rats undergo stereotaxic surgery and an electrode is implanted in the right lateral habenula. Following a ten day recovery period, rats (kept at 80 percent body weight) are tested for the number of chocolate chips consumed during a 10 minute period of time both with and without electrical stimulation. The testing conditions are counter balanced. Compute the appropriate t-test for the data provided below.

1 .What is your computed answer? tobs = 1.315

2. What would be the null hypothesis in this study? Electrical stimulation of the lateral habenula has no impact on food intake; there will be no difference in the amount of chocolate chips consumed. 3. What would be the alternate hypothesis? Electrical stimulation of the lateral habenula will have an impact on food intake either increasing or decreasing the amount of chocolate chips consumed. 4. What probability level did you choose and why? .05 There is little risk involved if either a Type I or a Type II error is made. 5. What were your degrees of freedom? N-1 = 9 6. Is there a significant difference between the two testing conditions? There is no significant difference between the amount of chocolate chips consumed. The tobs fall in the middle section of the tdistribution. 7. Interpret your answer. Electrical stimulation appears to have no impact on the amount of chocolate chips consumed by the rat (t=1.315, not significant). 8. If you have made an error, would it be a Type I or a Type II error? Explain your answer. If an error was made, it would have to be a Type II error as we found no differences. It may be that the lateral habenula does play a role in food intake but we failed to demonstrate it with this study/sample.

ANOVA PRACTICE PROBLEM
A researcher is concerned about the level of knowledge possessed by university students regarding United States history. Students completed a high school senior level standardized U.S. history exam. Major for students was also recorded. Data in terms of percent correct is recorded below for 32 students. Compute the appropriate test for the data provided below.

1. What is your computed answer? F = .04 (3,28), not significant 2. What would be the null hypothesis in this study? There will be no difference in history test scores between students with different academic major. 3. What would be the alternate hypothesis? There will be a difference somewhere in history scores between the four groups with different academic major. 4. What probability level did you choose and why? p = .05 There is little risk involved if either a Type I or a Type II major is made. 5. What were your degrees of freedom? 3, 28

6. Is there a significant difference between the four testing conditions? No significant differences were found between the four groups in terms of performance on a U.S. history exam. 7. Interpret your answer. Students regardless of academic major performed equally (in this case poorly) on a high school senior standardized U.S. history exam. 8. If you have made an error, would it be a Type I or a Type II error? Explain your answer. If I have made an error, it would be a Type II error. There really is a difference in history knowledge between academic major but somehow I failed to demonstrate that with this study.

LINEAR REGRESSION PRACTICE PROBLEM
Researchers interested in determining if there is a relationship between death anxiety and religiosity conducted the following study. Subjects completed a death anxiety scale (high score = high anxiety) and also completed a checklist designed to measure an individuals degree of religiosity (belief in a particular religion, regular attendance at religious services, number of times per week they regularly pray, etc.) (high score = greater religiosity . A data sample is provided below:

1. What is your computed answer? r = -.696069034 or -.70 2. What does this statistic mean concerning the relationship between death anxiety and religiosity? There is a moderate to strong correlation between death anxiety and religiousity. Individuals with high levels of religiosity have lower levels of death anxiety and vice versa. We can not say that participation in religious activities causes lower levels of death anxiety as one can not draw this sort of cause and effect conclusion based on a correlational study. 3. What percent of the variability is accounted for by the relation of these two variables? r2 = .48

CHI SQUARE PRACTICE PROBLEM
A marketing firm producing detergents is interested in studying the consumer behavior in the context of purchase decision of detergents in a specific market. This company is a major player in the detergent market that is characterized by intense competition. It would like to know in particular whether the income level of the consumers influence their choice of the brand. Currently there are four brands in the market. Brand 1 and Brand 2 are the premium brands while Brand 3 and Brand 4 are the economy brands. A representative stratified random sampling procedure was adopted covering the entire market using income as the basis of selection. The categories that were used in classifying income level are: Lower, Middle, Upper Middle and High. A sample of 600 consumers participated in this study. The following data emerged from the study.

Solution: Null Hypothesis: There is no association between the brand preference and income level (These two attributes are independent). Alternative Hypothesis: There is association between brand preference and income level (These two attributes are dependent). Let us take a level of significance of 5%. The critical value of c² depends on the degrees of freedom. The degrees of freedom = (the number of rows-1) multiplied by (the number of colums-1) in any contingency table. In our case, there are 4 rows and 4 columns. So the degrees of freedom =(4-1). (4-1) =9. At 5% level of significance, critical c² for 9 d.f = 16.92. Therefore reject the null hypothesis and accept the alternative hypothesis. The inference is that brand preference is highly associated with income level. Thus, the choice of the brand depends on the income strata. Consumers in different income strata prefer different brands. Specifically, consumers in upper middle and upper income group prefer premium brands while consumers in lower income and middle-income category prefer economy brands. The company should develop suitable strategies to position its detergent products. In the marketplace, it should position economy brands to lower and middle-income category and premium brands to upper middle and upper income category.

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