STATISTICAL ANALYSIS

Statistical Analysis

Statistical Analysis

Min

6.7

7.9

15

20

0

3

55

141

1

2

3800

1695

Max

45.4

80

46

50

2

8

300

219

5.7

8

6500

4105

Mean

17.13

21.90

22.37

29.09

0.81

4.97

143.83

183.20

2.67

5.09

5280.65

3072.90

Median

14.70

19.60

21.00

28.00

1.00

4.00

140.00

183.00

2.40

5.00

5200.00

3040.00

Mode

14.20

21.70

18.00

26.00

1.00

4.00

110.00

184.00

3.00

5.00

6000.00

3470.00

St Dev

8.75

11.03

5.62

5.33

0.71

1.30

52.37

14.60

1.04

1.04

596.73

589.90

coef of var

0.51

0.50

0.25

0.18

0.88

0.26

0.36

0.08

0.39

0.20

0.11

0.19

Skewness

1.18

2.03

1.70

1.23

0.30

0.82

0.95

-0.09

0.86

0.06

-0.26

-0.14

Count

93.00

93.00

93.00

93.00

93.00

92.00

93.00

93.00

93.00

93.00

93.00

93.00

VAR00001

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

3

2

4.4

4.4

4.4

7

1

2.2

2.2

6.7

9

1

2.2

2.2

8.9

11

1

2.2

2.2

11.1

12

1

2.2

2.2

13.3

13

1

2.2

2.2

15.6

15

1

2.2

2.2

17.8

16

1

2.2

2.2

20.0

17

1

2.2

2.2

22.2

18

1

2.2

2.2

24.4

19

2

4.4

4.4

28.9

20

1

2.2

2.2

31.1

21

2

4.4

4.4

35.6

22

5

11.1

11.1

46.7

23

5

11.1

11.1

57.8

24

5

11.1

11.1

68.9

25

2

4.4

4.4

73.3

26

3

6.7

6.7

80.0

27

2

4.4

4.4

84.4

28

3

6.7

6.7

91.1

29

1

2.2

2.2

93.3

30

2

4.4

4.4

97.8

33

1

2.2

2.2

100.0

Total

45

100.0

100.0

Above frequency table shows that the values, 22, 23, and 24 have maximum frequencies in the data.

(b)

Comments on histogram

Histogram shows that data is negatively skewed as most of the bars of histogram falls on the right side and maximum values are between 20 and 30.

Q.2(a) solution:

Comments on histograms:

Histograms show a significant change in unit sales for vehicles from March 2006 to March 2007. As the above diagram shows that there is a consistency in the sales in earlier months of year 2007 but at the end i.e. in Feb and March sales have shoot up to a record level.

Question 3 Solution: (a)

Statistics

graduates

non-graduates

N

Valid

10

10

Missing

0

0

Mean

2.1300E4

14600.0000

Median

2.1000E4

14500.0000

Percentiles

25

1.7750E4

12750.0000

50

2.1000E4

14500.0000

75

2.4750E4

16250.0000

(b)

Statistics

graduates

non-graduates

N

Valid

10

10

Missing

0

0

Std. Deviation

4.16467E3

2366.43191

Range

13000.00

8000.00

(c) Above table shows a significant difference in the annual salaries of graduates and non graduates, as the salaries of graduates are more than double as compared with the salaries

Of the non graduates.

Q4 solution: (a)

Statistics

waiters

waitresses

N

Valid

4

4

Missing

6

6

Mean

30.0000

7.5000

Median

30.0000

8.0000

Std. Deviation

1.29099E1

3.41565

Range

30.00

8.00

(b)

There is no proper shape of distribution to be followed but majority of points fall near to centre diagonal so we can use normal distribution.

(c)

Statistics

waiters

N

Valid

4

Missing

6

Mean

30.0000

Std. Deviation

1.29099E1

Statistics

waiteresses

N

Valid

4

Missing

6

Mean

7.5000

Std. Deviation

3.41565

(d)

Ratio Statistics for waiters / waiteresses

Minimum

2.143

Maximum

15.000

Std. Deviation

6.167

Price Related Differential

1.457

Coefficient of Dispersion

1.174

Coefficient of Variation

Median Centered

225.1%

Q 5 Answer: Introduction

Quantitative research is all about quantifying relationships between variables. Variables are things like weight, performance, time, and treatment. You measure variables on a sample of subjects, which can be tissues, cells, animals, or humans. You express the relationship between variable using effect statistics, such as correlations, relative frequencies, or differences between means. I deal with these statistics and other aspects of analysis elsewhere at this site. In this article I focus on the design of quantitative research. First I describe the types of study you can use. Next I discuss how the nature of the sample affects your ability to make statements about the relationship in the population. I then deal with various ways to work out the size of the sample. Finally I give advice about the kinds of variable you need to measure.( Andreasen , 1995)

Qualitative process evaluation methods can include periodic interviews or focus groups with target audience members to assess their progress toward behavior change. Through these activities, participants may inform program administrators of unforeseen barriers or opportunities to adopting the behavior that need to be addressed to increase chances of success. Observations of audience members may also provide clues to needed changes in program strategy or messages ...