Quantitative Data Analysis
Content
Bar Chart
Table 1: Cocoa Production of selected countries in Africa for 20
1,400,000
Country
Ghana
Nigeria
Cote d' Ivoire
Togo
Guinea
Benin
Output in tonnes
1,000,000
560,000
1,240,000
Output in tonnes
150,000
200,000
70,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
Ghana
Nigeri
r Chart
in Africa for 2010
0,000
0,000
0,000
0,000
0,000
Output in tonnes
0,000
0,000
0
Ghana
Nigeria Cote d' Ivoire
Country
Togo
Guinea
Benin
Table 2: Cocoa Production in Ghana between 2000 and 2010
Year
Output in tonnes
2000
750,000.00
2001
770,000.00
2002
670,000.00
2003
700,000.00
2004
800,000.00
2005
820,000.00
2006
950,000.00
2007
960,000.00
2008
970,000.00
2009
985,000.00
2010 1,000,000.00
1,200,000.00
1,000,000.00
800,000.00
Output in tonnes
600,000.00
400,000.00
200,000.00
-
2000200120
Line graph
en 2000 and 2010
utput in tonnes
1,200,000.00
1,000,000.00
800,000.00
600,000.00
Output in tonnes
400,000.00
200,000.00
20002001200220032004200520062007200820092010
Year
820092010
Output in tonnes
Assume you collect the following data on customer spending per visit
Customer ID
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
spending
21
24.3
23
24.8
22
24.9
24
25
25.8
29.8
27
30
31.1
30.6
38
34
37
45
42
44.5
48.2
46
47
43.7
22.5
21
24.8
26
34
30
31
20.9
You can notice that the data on
customer spending is a continuous
data as a customers spending take
on any value including decimals.
We can use histogram to represent
this.
The prices ranges from GHC20 to
about GHC50
Lets put the prices in groups of GHC
5 apart; i.e.
GHC 20 to just below 25
25 to just below 30
30 to just below 35
35 to just below 40
40 to just belwo 45
45 to just below 50
To make counting the frequency for
each group above easier, put the
data on spending in order from
lowest to highest as shown in Table
2.
spending per visit at Woollon's supermarket for the period of 11-17th Februa
Table 2
Customer ID
32
1
26
5
25
3
7
2
4
27
6
8
9
28
11
10
12
30
14
31
13
16
29
17
15
19
24
20
18
22
23
21
spending
20.9
21
21
22
22.5
23
24
24.3
24.8
24.8
24.9
25
25.8
26
27
29.8
30
30
30.6
31
31.1
34
34
37
38
42
43.7
44.5
45
46
47
48.2
Spending
20 to <25
25 to <30
30 to <35
35 to <40
40 to <45
45 to <50
12
10
8
6
Frequency (Number of Customers)
4
2
0
period of 11-17th February 2008
Frequency (Number of customers)
y (Number of Customers)
11
5
7
2
3
4
12
10
8
6
4
2
0
Amount Spent per visit in GHC
XYZ Ltd: Breakdown of Sales by region in 2007
Product
Sales in GHC
Pepsodent
Keysoap
Lux
Geisha
Frytol
1,600,000.00
800,000.00
500,000.00
650,000.00
1,400,000.00
In using a pie chart, we usually use
percentages.
So calculate the percentage for
each product. The total percentage
should add to 100%
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Total
Sales in GHC
1,600,000.00
800,000.00
500,000.00
650,000.00
1,400,000.00
4,950,000.00
32%
16%
10%
13%
28%
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Sales (%)
32%
16%
10%
13%
28%
Frytol; 28%
Geisha; 13%
Lux; 10%
Pepsodent; 32%
Keysoap; 16%
Total Sales = GHC 4,950,000
COMPARATIVE PROPORTIO
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
2007
Sales (%)
32%
16%
10%
13%
28%
Frytol; 28%
Geisha; 13%
Pepsodent; 32%
Keysoap; 16%
Lux; 10%
2007: Total Sales = GHC 4,950,000
PERCENTAGE COMPONENT
To draw the component bar chart we would need to put the three tables above together
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
2007
32%
2008
40%
2009
51%
16%
10%
13%
28%
12%
13%
20%
15%
12%
7%
15%
15%
100%
90%
80%
28%
70%
60%
50%
40%
13%
10%
16%
30%
20%
10%
0%
32%
2007
EXAMPLE 2
Responses to "Would you purchase this product again?".
Product
Product A
Product B
Product C
Product D
Definitely
50%
40%
30%
37%
Probably
35%
30%
45%
39%
Unsure
15%
10%
18%
4%
No
0%
20%
7%
20%
100%
100%
100%
100%
MPARATIVE PROPORTIONAL PIE CHARTS COMPARING BOTH PROPORTIONS AND TOTALS BETWEEN
2008
Product Sales (%)
Pepsodent
40%
Keysoap
12%
Lux
13%
Geisha
20%
Frytol
15%
2009
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Frytol; 15%
Geisha; 20%
Lux; 13%
F
Pepsodent; 40%
Geisha;
Lux;
Ke
Keysoap; 12%
2008: Total Sales = GHC 3,874,000
2009: T
RCENTAGE COMPONENT BAR CHART - USED TO COMPARE PROPORTIONS BETWEEN VARIABLES
above together
100%
90%
80%
50%
40%
15%
20%
15%
7%
28%
70%
60%
15%
13%
10%
13%
12%
Keysoap
16%
Pepsodent
20%
0%
Geisha
Lux
12%
30%
10%
Frytol
32%
40%
51%
2007
2008
2009
100%
90%
80%
70%
60%
Product D
50%
Product C
40%
Product B
Product A
30%
20%
10%
0%
Definitely
Probably
Unsure
No
X
Which of the two graphs is more appropriate?
What can we do to enhance the graph you choose?
D TOTALS BETWEEN VARIABLES
2009
Sales (%)
51%
12%
7%
15%
15%
Frytol; 15%
Geisha; 15%
Pepsodent; 51%
Lux; 7%
Keysoap; 12%
2009: Total Sales = GHC 5,101,800
WEEN VARIABLES
Enhance this graph
Product D
Product C
Percentage of Respondents
Product B
Product A
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0%
15%
35%
20%
10%
30%
7%
18%
45%
39%
No
50%
40%
30%
37%
Unsure
Probably
Definitely
Product
Y
20%
4%
No
Unsure
Probably
Definitely
STACKED BAR CHART OR COMPONENT BAR CH
Company A
Company B
Company C
Sales by quarter in $ million
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
115
140
150
130
115
150
155
145
120
170
165
150
Total
535
565
605
If we were interested in comparing proportions by quarter across the companies,
then we could transform the data into percentages and use a percentage component bar chart
T OR COMPONENT BAR CHARUSED TO COMPARE TOTALS BETWEEN VARIABLES
700
600
500
130
145
400
Sales in $ million
ompanies,
ge component bar chart
300
200
150
165
150
155
140
150
170
115
115
120
Company A
Company B
Company C
4th Qtr
3rd Qtr
100
0
Company
2nd Qtr
1st Qtr
MULTIPLE BAR CHART
- Comparisons of variables th
Exports and Imports for country XYZ for 2000 - 2004
Years
Export
2000
2001
2002
2003
2004
4,100
5,200
8,000
7,500
2,300
Import
12,100
9,050
9,800
11,190
10,000
Export and Impo
14,000
12,000
10,000
8,000
Amount in $million
6,000
4,000
2,000
-
200
risons of variables that emphasise the highest and lowest rather than precise values
Export and Import for 2000 - 2004
$million
14,000
12,000
10,000
8,000
Export
6,000
Import
4,000
2,000
-
2000
2001
2002
Year
2003
2004
n precise values
CONTIGENCY TABLEto show specific values
Table 12.3: Number of insurance claims by gender, 2008
Number of claims*
Male
Female
Total
0
10032
13478
23510
1
2156
1430
3586
2
120
25
145
3
13
4
17
Total
12321
14937
27258
*No clients had more than three claims
Source: PJ Insurance Services
MULTIPLE LINE GRAPH to compare trends for two or more v
Month
Jan-07
Feb-07
Mar-07
Apr-07
May-07
Jun-07
Jul-07
Aug-07
Sep-07
Oct-07
Nov-07
Dec-07
Jan-08
Feb-08
Mar-08
Apr-08
May-08
Jun-08
Jul-08
Aug-08
Sep-08
Oct-08
Nov-08
Dec-08
Chocolate
Vanilla
11
10
10
12
14
15
17
18.5
12
11
10
11.5
12
12
13
15
17
22
24
21
18
12.5
12
12.5
Strawberry
5
4.5
6
4
6
4
7.5
5
8
6
9
7
10.1
8.5
11.5
9
10.1
8.8
7
5.5
6
5
6.5
6
7
7
7
7
8
7.5
9
8
10
9
13.5
13
14.5
14
13
12.5
12
11.8
8.5
7.5
7.5
7
8
9
30
25
20
15
Sales in 000 litres
10
5
0
e trends for two or more variables
30
25
20
15
Sales in 000 litres
Chocolat
10
Vanilla
Strawber
5
0
Month
Chocolate
Vanilla
Strawberry
SCATTER GRAPH
to show relationship bet
Exploring the relationship between price and units purchased of Product A, 2007
Price in GHC
10
15
20
25
30
35
40
Units purchased
167
149
135
108
82
55
23
180
160
140
120
100
Units purchased
80
60
40
20
0
5
10
o show relationship between two variables
s purchased
180
This graph shows a neg
between price and the
160
140
120
100
80
Units purchased
60
40
20
0
5
10
15
20
25
30
Price in GHC
35
40
45
his graph shows a negative relationship
etween price and the units purchased
Table 1: Cocoa Production of selected countries in Africa for 20
1,400,000
Country
Ghana
Nigeria
Cote d' Ivoire
Togo
Guinea
Benin
Output in tonnes
1,000,000
560,000
1,240,000
Output in tonnes
150,000
200,000
70,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
Ghana
Nigeri
r Chart
in Africa for 2010
0,000
0,000
0,000
0,000
0,000
Output in tonnes
0,000
0,000
0
Ghana
Nigeria Cote d' Ivoire
Country
Togo
Guinea
Benin
Table 2: Cocoa Production in Ghana between 2000 and 2010
Year
Output in tonnes
2000
750,000.00
2001
770,000.00
2002
670,000.00
2003
700,000.00
2004
800,000.00
2005
820,000.00
2006
950,000.00
2007
960,000.00
2008
970,000.00
2009
985,000.00
2010 1,000,000.00
1,200,000.00
1,000,000.00
800,000.00
Output in tonnes
600,000.00
400,000.00
200,000.00
-
2000200120
Line graph
en 2000 and 2010
utput in tonnes
1,200,000.00
1,000,000.00
800,000.00
600,000.00
Output in tonnes
400,000.00
200,000.00
20002001200220032004200520062007200820092010
Year
820092010
Output in tonnes
Assume you collect the following data on customer spending per visit
Customer ID
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
spending
21
24.3
23
24.8
22
24.9
24
25
25.8
29.8
27
30
31.1
30.6
38
34
37
45
42
44.5
48.2
46
47
43.7
22.5
21
24.8
26
34
30
31
20.9
You can notice that the data on
customer spending is a continuous
data as a customers spending take
on any value including decimals.
We can use histogram to represent
this.
The prices ranges from GHC20 to
about GHC50
Lets put the prices in groups of GHC
5 apart; i.e.
GHC 20 to just below 25
25 to just below 30
30 to just below 35
35 to just below 40
40 to just belwo 45
45 to just below 50
To make counting the frequency for
each group above easier, put the
data on spending in order from
lowest to highest as shown in Table
2.
spending per visit at Woollon's supermarket for the period of 11-17th Februa
Table 2
Customer ID
32
1
26
5
25
3
7
2
4
27
6
8
9
28
11
10
12
30
14
31
13
16
29
17
15
19
24
20
18
22
23
21
spending
20.9
21
21
22
22.5
23
24
24.3
24.8
24.8
24.9
25
25.8
26
27
29.8
30
30
30.6
31
31.1
34
34
37
38
42
43.7
44.5
45
46
47
48.2
Spending
20 to <25
25 to <30
30 to <35
35 to <40
40 to <45
45 to <50
12
10
8
6
Frequency (Number of Customers)
4
2
0
period of 11-17th February 2008
Frequency (Number of customers)
y (Number of Customers)
11
5
7
2
3
4
12
10
8
6
4
2
0
Amount Spent per visit in GHC
XYZ Ltd: Breakdown of Sales by region in 2007
Product
Sales in GHC
Pepsodent
Keysoap
Lux
Geisha
Frytol
1,600,000.00
800,000.00
500,000.00
650,000.00
1,400,000.00
In using a pie chart, we usually use
percentages.
So calculate the percentage for
each product. The total percentage
should add to 100%
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Total
Sales in GHC
1,600,000.00
800,000.00
500,000.00
650,000.00
1,400,000.00
4,950,000.00
32%
16%
10%
13%
28%
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Sales (%)
32%
16%
10%
13%
28%
Frytol; 28%
Geisha; 13%
Lux; 10%
Pepsodent; 32%
Keysoap; 16%
Total Sales = GHC 4,950,000
COMPARATIVE PROPORTIO
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
2007
Sales (%)
32%
16%
10%
13%
28%
Frytol; 28%
Geisha; 13%
Pepsodent; 32%
Keysoap; 16%
Lux; 10%
2007: Total Sales = GHC 4,950,000
PERCENTAGE COMPONENT
To draw the component bar chart we would need to put the three tables above together
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
2007
32%
2008
40%
2009
51%
16%
10%
13%
28%
12%
13%
20%
15%
12%
7%
15%
15%
100%
90%
80%
28%
70%
60%
50%
40%
13%
10%
16%
30%
20%
10%
0%
32%
2007
EXAMPLE 2
Responses to "Would you purchase this product again?".
Product
Product A
Product B
Product C
Product D
Definitely
50%
40%
30%
37%
Probably
35%
30%
45%
39%
Unsure
15%
10%
18%
4%
No
0%
20%
7%
20%
100%
100%
100%
100%
MPARATIVE PROPORTIONAL PIE CHARTS COMPARING BOTH PROPORTIONS AND TOTALS BETWEEN
2008
Product Sales (%)
Pepsodent
40%
Keysoap
12%
Lux
13%
Geisha
20%
Frytol
15%
2009
Product
Pepsodent
Keysoap
Lux
Geisha
Frytol
Frytol; 15%
Geisha; 20%
Lux; 13%
F
Pepsodent; 40%
Geisha;
Lux;
Ke
Keysoap; 12%
2008: Total Sales = GHC 3,874,000
2009: T
RCENTAGE COMPONENT BAR CHART - USED TO COMPARE PROPORTIONS BETWEEN VARIABLES
above together
100%
90%
80%
50%
40%
15%
20%
15%
7%
28%
70%
60%
15%
13%
10%
13%
12%
Keysoap
16%
Pepsodent
20%
0%
Geisha
Lux
12%
30%
10%
Frytol
32%
40%
51%
2007
2008
2009
100%
90%
80%
70%
60%
Product D
50%
Product C
40%
Product B
Product A
30%
20%
10%
0%
Definitely
Probably
Unsure
No
X
Which of the two graphs is more appropriate?
What can we do to enhance the graph you choose?
D TOTALS BETWEEN VARIABLES
2009
Sales (%)
51%
12%
7%
15%
15%
Frytol; 15%
Geisha; 15%
Pepsodent; 51%
Lux; 7%
Keysoap; 12%
2009: Total Sales = GHC 5,101,800
WEEN VARIABLES
Enhance this graph
Product D
Product C
Percentage of Respondents
Product B
Product A
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
0%
15%
35%
20%
10%
30%
7%
18%
45%
39%
No
50%
40%
30%
37%
Unsure
Probably
Definitely
Product
Y
20%
4%
No
Unsure
Probably
Definitely
STACKED BAR CHART OR COMPONENT BAR CH
Company A
Company B
Company C
Sales by quarter in $ million
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
115
140
150
130
115
150
155
145
120
170
165
150
Total
535
565
605
If we were interested in comparing proportions by quarter across the companies,
then we could transform the data into percentages and use a percentage component bar chart
T OR COMPONENT BAR CHARUSED TO COMPARE TOTALS BETWEEN VARIABLES
700
600
500
130
145
400
Sales in $ million
ompanies,
ge component bar chart
300
200
150
165
150
155
140
150
170
115
115
120
Company A
Company B
Company C
4th Qtr
3rd Qtr
100
0
Company
2nd Qtr
1st Qtr
MULTIPLE BAR CHART
- Comparisons of variables th
Exports and Imports for country XYZ for 2000 - 2004
Years
Export
2000
2001
2002
2003
2004
4,100
5,200
8,000
7,500
2,300
Import
12,100
9,050
9,800
11,190
10,000
Export and Impo
14,000
12,000
10,000
8,000
Amount in $million
6,000
4,000
2,000
-
200
risons of variables that emphasise the highest and lowest rather than precise values
Export and Import for 2000 - 2004
$million
14,000
12,000
10,000
8,000
Export
6,000
Import
4,000
2,000
-
2000
2001
2002
Year
2003
2004
n precise values
CONTIGENCY TABLEto show specific values
Table 12.3: Number of insurance claims by gender, 2008
Number of claims*
Male
Female
Total
0
10032
13478
23510
1
2156
1430
3586
2
120
25
145
3
13
4
17
Total
12321
14937
27258
*No clients had more than three claims
Source: PJ Insurance Services
MULTIPLE LINE GRAPH to compare trends for two or more v
Month
Jan-07
Feb-07
Mar-07
Apr-07
May-07
Jun-07
Jul-07
Aug-07
Sep-07
Oct-07
Nov-07
Dec-07
Jan-08
Feb-08
Mar-08
Apr-08
May-08
Jun-08
Jul-08
Aug-08
Sep-08
Oct-08
Nov-08
Dec-08
Chocolate
Vanilla
11
10
10
12
14
15
17
18.5
12
11
10
11.5
12
12
13
15
17
22
24
21
18
12.5
12
12.5
Strawberry
5
4.5
6
4
6
4
7.5
5
8
6
9
7
10.1
8.5
11.5
9
10.1
8.8
7
5.5
6
5
6.5
6
7
7
7
7
8
7.5
9
8
10
9
13.5
13
14.5
14
13
12.5
12
11.8
8.5
7.5
7.5
7
8
9
30
25
20
15
Sales in 000 litres
10
5
0
e trends for two or more variables
30
25
20
15
Sales in 000 litres
Chocolat
10
Vanilla
Strawber
5
0
Month
Chocolate
Vanilla
Strawberry
SCATTER GRAPH
to show relationship bet
Exploring the relationship between price and units purchased of Product A, 2007
Price in GHC
10
15
20
25
30
35
40
Units purchased
167
149
135
108
82
55
23
180
160
140
120
100
Units purchased
80
60
40
20
0
5
10
o show relationship between two variables
s purchased
180
This graph shows a neg
between price and the
160
140
120
100
80
Units purchased
60
40
20
0
5
10
15
20
25
30
Price in GHC
35
40
45
his graph shows a negative relationship
etween price and the units purchased
