BB108 Business Statistics For Satisfaction Level Of Global Corporation Essay

Questions:

a.Understand fundamentals of statistics and its application in business
b.Assess when and how to use statistical analysis.
c.Solve statistical problems using analytical methods.
d.Apply knowledge of related statistical analytical techniques as related to business problems.

Answer:

Introduction

The present report analysis the job satisfaction level of Global corporation. The employees of the organization received training in order to improve their level of job satisfaction. As such to estimate the effect of the training information had been collected from a sample of 300 employees. The information pertains to employees from different departments, regions, city area, age gender and marital status. The effect of training on job satisfaction for both sexes and on the whole sample has been evaluated.

Problem Definition and Business Intelligence Required

Global corporation is a large organization with offices in different regions of the city and city area. The organization desires to investigate the level of job satisfaction of its employees. Towards this goal the organization collected the job satisfaction information from its employees. They found that the level of job satisfaction is very poor. As such the organization provided training and again measured the job satisfaction. The organization seeks to investigate the effect of the training on job satisfaction. As such they company collected information from 300 employees.

In order to evaluate the level of job satisfaction descriptive statistics have been used to study the variables Age, Years of experience and Salary. Frequency analysis has been used to study other information.

Identifying the Data Variables as Measures of Scales and Data Types

The data type for the different variables for which information has been collected are:

Variable

Data Type

Gender

Nominal

Age

Ratio Scale

Marital Status

Ordinal

Experience

Continuous Variable in interval Scale

City

Nominal

Region of the employees

Nominal

Departments

Nominal

Salary

Continuous Variable in interval Scale

Job Satisfaction before training

Ordinal Scale

Job Satisfaction after training

Ordinal Scale

Count of Life Happiness

Ordinal Scale

Promotion

Nominal Scale

Descriptive Statistics

The frequency of the variables are as follows:

Gender

Marital Status

Male

114

Married

252

Female

186

Single

48

City Area

1

82

2

63

3

46

4

73

5

36

Region

East

71

West

123

North

47

South

59

Scores

Job Satisfaction Score before training(1-5)

Job Satisfaction Score after training(1-5)

1

93

8

2

112

31

3

69

134

4

24

44

5

2

83

Promoted

Yes

190

No

110

Life Scores

1

50

2

36

3

35

4

21

5

59

6

31

8

19

9

33

10

16

Descriptive statistics of Age, Years of Experience and Salary of the employees:

Statistics

Age

Years of experience

Salary(000)

Mean

41.88

20.71

47.36

Standard Error

0.59

0.55

0.39

Median

42

23

47

Mode

54

25

45

Standard Deviation

10.18

9.54

6.68

Sample Variance

103.61

90.97

44.59

Kurtosis

-0.93

-0.95

0.02

Skewness

-0.16

-0.41

-0.10

Range

40

35

39

Minimum

20

1

26

Maximum

60

36

65

1st Quartile

32

13

44

3rd Quartile

50

28

52

IQR

18

15

8

Sum

12564

6212

14208

Count

300

300

300

The descriptive statistics indicates that the mean and median age of the employees are 41.88 and 42 respectively. The Age of the employees ranges from 20 to 60. Similarly, the mean and median years of experience of the employees is 20.71 and 23 respectively. The minimum and maximum years of experience are 1 and 36 respectively. Further it is found that the mean and median salary of the employees is 47.36 and 47 respectively.

Method of Data Summarising

Job Satisfaction before and after training

In order to analyse for differences in job satisfaction before and after training the dependent sample t-test is used. A 0.05 level of significance is used to evaluate the differences.

Job Satisfaction Score before training(1-5)

Job Satisfaction Score after training(1-5)

Mean

2.10

3.54

Variance

0.91

1.17

Observations

300

300

Pearson Correlation

-0.06

Hypothesized Mean Difference

0

df

299

t Stat

-16.826

P(T<=t) one-tail

0.000

t Critical one-tail

1.650

P(T<=t) two-tail

0.000

t Critical two-tail

1.968

From the paired sample t-test it can be inferred there is statistically significant differences between mean job satisfaction score after training (3.54) and mean job score before training (2.10), p-value < 0.000 at 0.05 level of significance

Job Satisfaction before and after training (Gender-Male)

In order to analyse for differences in job satisfaction before and after training for males the dependent sample t-test is used. A 0.05 level of significance is used to evaluate the differences.

Before Training

After Training

Mean

2.193

3.482

Variance

0.989

1.243

Observations

114

114

Pearson Correlation

-0.021

Hypothesized Mean Difference

0

df

113

t Stat

-9.121

P(T<=t) one-tail

0.000

t Critical one-tail

1.658

P(T<=t) two-tail

0.000

t Critical two-tail

1.981

From the paired sample t-test it can be inferred there is statistically significant differences between mean job satisfaction score after training (3.482) and mean job score before training (2.193) for males, p-value < 0.000 at 0.05 level of significance

Job Satisfaction before and after training (Gender-Female)

In order to analyse for differences in job satisfaction before and after training for females the dependent sample t-test is used. A 0.05 level of significance is used to evaluate the differences.

Before Training

After Training

Mean

2.043

3.581

Variance

0.863

1.131

Observations

186

186

Pearson Correlation

-0.080

Hypothesized Mean Difference

0

df

185

t Stat

-14.293

P(T<=t) one-tail

0.000

t Critical one-tail

1.653

P(T<=t) two-tail

0.000

t Critical two-tail

1.973

From the paired sample t-test it can be inferred there is statistically significant differences between mean job satisfaction score after training (3.581) and mean job score before training (2.043) for females, p-value < 0.000 at 0.05 level of significance

Age differences between Gender

In order to analyse for differences in age between males and females the independent sample t-test is used. A 0.05 level of significance is used to evaluate the differences.

Female

Male

Mean

39.989

44.965

Variance

87.892

114.778

Observations

186

114

Pooled Variance

98.087

Hypothesized Mean Difference

0

df

298

t Stat

-4.224

P(T<=t) one-tail

0.000

t Critical one-tail

1.650

P(T<=t) two-tail

0.000

t Critical two-tail

1.968

From the independent sample t-test it can be inferred that the mean age of males (44.965) is more than the mean age of females (39.989), at 0.05 level of significance, p-value <0.000.

Results and Recommendations

From the analysis of the job satisfaction scores it is seen that there has been significant improvement in job satisfaction after training. Moreover, the improvement in job satisfaction is both males and females. In addition, the analysis of the information shows that the mean age of males is more than the mean age of females.

Thus it can be recommended that since there has been significant improvement in job satisfaction after the training thus the organization should schedule more training to improve the level of job satisfaction of the employees.

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