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Sta 2023 : Statistics : Assessment Answers

1. Before you begin your analysis you are required to take a random sample of size 100from the 171 cases in the data file. Use the Data and Generator.xls to do this. Open this file and go to the first worksheet labelled Macro. Click on Generate and enter the number of rows of data required in the random sample. If you have repeated cases your final sample size may be less than 100. This will not be a problem. Answers to the questions below are to be based on this random sample of up to 100 cases. Make sure you keep a safe copy of your sample since you cannot use the Random Sample Generator to reproduce the first sample. 

2. Data List:Provide a printout of the data in your sample, with ID numbers in ascending order. 

3. Introduction and Variable List: Provide a summary table listing each variable with informationunder the following column headings: Variable Name, Variable Description (see the information above) and Variable Type (qualitative or quantitative). If the variable is qualitative state whether it is nominal or ordinal; if it is quantitative you need to state whether it is discrete or continuous. 

4. Descriptive statistics: Historically the company believed that average salary of male is greaterthan the average salary of female. Determine the mean, median, and standard deviation of current salary data for male and female. Explain the results in the context of the company’s believe. (10 marks)

5. Presentation of data: Draw Histogram and Boxplots for both male and female for current salary Explain the graphs. (10 marks)

PART 2:

6.Hypothesis testing: Use the above information to carry out a t-test to see the averagecurrent salary for male is significantly greater than the average current salary for female.

Explain the result in the light of the question. 

7.Comparing gender and positions:

Prepare a Pivot table that shows average current salary for males and females according to their Position within the company. Think carefully about the layout of rows and columns of your table. Place gender in row, positions in column, and current salaries in value box. Then summarise values as average. Explain the results. 

8.Comparing Departments: The head of Human Resources wants to compare the structure of thefour departments by gender within the Company.

a.Draw a Pivot table with gender in row, department in column and gender in value. 
b.Determine the joint probability for gender and department. Explain the result. 
c.Determine the marginal probability and explain the result. 
d.Determine the conditional probability by column and explain the result.
e.Determine the conditional probability by row and explain the result. 

PART 3:

9.Average salary increase per year: There have been complaints in this company that femaleemployees have been given lower salary increases than their male colleagues.

Examine the issue: Have the salary increases for females been lower?

a). Create a new column, called Length Emplwhich shows the length of time a person has been employed in the company, as of the end of December 2014. Assume that if an employee started in 2008 than they have been employed for 6 years; if they started in 1997 than they have been employed for 17 years, and so on. Create a second new column, called Avg Incr which shows the average increase in salary for each employee since the year they started work for the company.  

State the formulae you have used to produce these new columns. Print out the ID column and the new data – 3 columns. This should be in ascending order of the ID numbers.

b). Use Avg Incrto create a histogram showing the distribution of the average salary increase per year. This histogram has been created to get some idea of the distribution of the data. Comment upon the shape of this distribution: Is it symmetric? Is it skewed? If so which way? (5 marks)

c). Now provide side by side boxplots for Avg Incr, split on gender. Again, comment on what you see. Most importantly, provide your answer to the question: “Have the salary increases for females beenlower than those for males?” (10 marks)

d). Run regression analysis with Start Salaryand Current Salary for both male and female separately. Check carefully which variable will be dependent variable and which variable will be independent variable Again comment on what you see. Most importantly, provide your answer to the question:

Have the salary increases for females been lower than those for males?” Comment whether the regression analyses support or oppose the conclusion in (c). 

10.Draw a suitable conclusion based on your data analysis.

 
 
1

A random data is derived through the macro developed for the generation of dataset. The dataset generated is saved in the excel sheet.

2

The sample data of 100 is presented in Appendix

3

Table 1: Summary Table of Variables

Variable Name

Variable Description

Variable Type

Gender

Prevalence of gender in the business

Qualitative - Nominal

Start Year

The year in which the employees started the job.

Quantitative - Discrete

Department

The department of the Employee.

Qualitative - Ordinal

Start Salary

The starting salary of the employees

Quantitative - Continuous

Current Salary

The present salary of the employees

Quantitative - Continuous

Years of Experience

The number of years of experience

Qualitative - Ordinal

Position

Based on the quality of work the current position of the employees.

Qualitative - Ordinal

 
4.
Table 2: Summary Statistics for Current salary

 

Male

Female

Mean

63180.79

64307.69

Median

60960

58920

Mode

63120

57120

Minimum

52080

42240

Maximum

119508

90600

Range

67428

48360

Variance

114606565.8

221572644.5

Standard Deviation

10705.45

14885.32

Coeff. of Variation

16.94

23.15

Skewness

3.21

0.47

Kurtosis

13.11

-1.11

Count

61

39

Standard Error

1370.69

2383.56

 

From the given sample it is found that the average salary of males and females is 63180.79 and 64307.69 respectively. Thus the belief of the company that the average salary of males is greater than females is found to be untrue for the current salary of the employees.

The deviation in males and females is 10705.45 and 14885.32 respectively. Thus, it can be seen that the variation in current salary for males is lower than females.

The median salary of males is 60960 while for females is 58920. Thus, it found that 50% of males gets below and above 60960. Similarly, 50% of the females get below and above 58920.

5). 

 

                                                                    Figure 1: Boxplot of Current Salary of Males and Females

From the above boxplot the distribution of current salary of Males and can be compared. It is found that the minimum salary of males is higher than females. Moreover, the maximum current salary of males is also higher than maximum current salary of females. The median current salary of males is slightly higher than females. It is also found that the current salary for both males and females is skewed right.

 

                                                                           Figure 2: Histogram of Current Salary of Males

From the histogram it can be seen that the distribution of the current salary of males is skewed right. Thus, the mean of the current salary is higher than the median salary.

                                                                        Figure 3: Histogram of Current Salary of Females

From the histogram it can be seen that the distribution of the current salary of females is skewed right. Thus, the mean of the current salary is higher than the median salary.

Part 2

6).

In order to analyse whether the average current salary of males is higher than females

Null Hypothesis: The average current salary of males and females are equal

Alternate Hypothesis: The average current salary of males is higher than females.

Table 3: Summary Statistics

Separate-Variances t Test for the Difference Between Two Means

(assumes unequal population variances)

Data

Hypothesized Difference

0

Level of Significance

0.05

Population 1 Sample

 

Sample Size

61

Sample Mean

63180.78689

Sample Standard Deviation

10705.4456

Population 2 Sample

 

Sample Size

39

Sample Mean

64307.69231

Sample Standard Deviation

14885.3164

 

Table 4: Independent Sample t-test

Upper-Tail Test

 

Upper Critical Value

1.6698

p-Value

0.6583

Do not reject the null hypothesis

 

Separate-Variance t Test Statistic

-0.4098

 

The average current salary of males is 63180.8 The average current salary of females is 64307.7.

From the independent sample t-test it is found that t(62) =-0.4098, p-value = 0.6583 at a = 0.05, level of significance.

The p-value is more than the level of significance. Hence we do not reject the Null hypothesis. Thus, the hypothesis test demonstrates that the average current salary of males and females are equal.

7).

Table 5: Relation of Average Current Salary to Gender and Position

Average of Current Salary

Position

 

Gender

1

2

3

Grand Total

Female

85080

85526

56036

64308

Male

97556

87660

60465

63181

Grand Total

90427

86000

58989

63620

 

From the above table it is found that the average current salary varies across gender and positions. For Males the average current salary is highest for position 1 followed by position 2 and the least is position 3. For females the average current salary is highest for Position 1, followed by Position 2 and the least for position 3.

Further, the average current salary for males is higher than females for all three positions.   

8).

Part a

Table 6: Count of Gender across Departments

 

Count of Gender

Department

 

Gender

1

2

3

4

Grand Total

Females

6

8

15

10

39

Males

9

27

10

15

61

Grand Total

15

35

25

25

100

 

From the above table it is found that for departments 1,2 and 4 the number of males is higher than females. In department 3 the number of females is higher than the number of males.

The sample dataset has the highest number of employees (35) from Department 2. Further, in the sample dataset the number of employees (25) from department 3 and 4 are equal.

Part b

 

Department

 

Gender

1

2

3

4

Total

Females

0.06

0.08

0.15

0.1

0.39

Males

0.09

0.27

0.1

0.15

0.61

Total

0.15

0.35

0.25

0.25

1

 

The joint probability provides information on proportion of gender in a department.

Thus the proportion of females in department 1 is 0.06. From the joint probability table, it is found that the lowest proportion of employees is females in department 1 – 0.06. The highest proportion of employees – males in department 2 is 0.27

Part c

 

Department

 

Gender

1

2

3

4

Total

Females

0.06

0.08

0.15

0.1

0.39

Males

0.09

0.27

0.1

0.15

0.61

Total

0.15

0.35

0.25

0.25

1

 

The marginal probabilities show that the proportion of females is to males is 0.39 to 0.69. Further, the proportion of employees in department 1, 2,3,4 is 0.15:0.35:0.25:0.25.

Part d

Count of Gender

Department

 

Gender

1

2

3

4

Grand Total

Females

40.00%

22.86%

60.00%

40.00%

39.00%

Males

60.00%

77.14%

40.00%

60.00%

61.00%

Grand Total

100.00%

100.00%

100.00%

100.00%

100.00%

 

The above table presents the conditional probability by column. The proportion of female employees in the organization is 39.0%. Similarly, the proportion of male employees in the organization is 61.0%.

Part e

Count of Gender

Department

 

Gender

1

2

3

4

Grand Total

Females

15.38%

20.51%

38.46%

25.64%

100.00%

Males

14.75%

44.26%

16.39%

24.59%

100.00%

Grand Total

15.00%

35.00%

25.00%

25.00%

100.00%

 

The above table presents the conditional probability by row. The proportion of employees in department 2 is the highest at 35.0%. The proportion of employees in department 3 and 4 are similar at 25.0%. The proportion of employees is department 1 is the lowest at 15.0%

Part 3

9).

Part a

A new variable “Length Empl” is created. To create the new column is MS-EXCEL we use the command:

  • =2014-C2

Here 2014 refers to the time when the management wants to know the duration of employment.

A second variable “Avg Incr” is created. The command used to create the variable:

  • =F2-E2

Where “F2” refers to the current salary of the employees and “E2” the starting salary of the employees.

The dataset is presented in Appendix.

Part b

 

Figure 4: Distribution of average Income

The distribution of average increase in Salary is left skewed. Thus the mean salary increase is greater than the median salary increase.

Part c

 

                                                               Figure 5: distribution of average increase in Salary based on gender

From the boxplot it is found that the average salary increase for both males and females is normally distributed. However, it is found that the minimum increase in Salary of females is higher than males. On the other hand, the maximum salary increase is more for males than females.

Thus for maximum salary increases the males have had a higher salary increase.

However, on the minimum scale, females have had a higher salary increase than males.

Part d

Females Salary

Calculations

b1, b0 Coefficients

0.8889

27641.4558

b1, b0 Standard Error

0.0585

2465.0302

R Square, Standard Error

0.7019

6828.0182

F, Residual df

230.7379

98.0000

Regression SS, Residual SS

10757426081.21

4568939654.95

 
 

Regression Statistics

Multiple R

0.8378

R Square

0.7019

Adjusted R Square

0.6988

Standard Error

6828.0182

Observations

100

 

Regression analysis is used to evaluate the current salary of females based on their starting salary. The starting salary is taken as the independent variable and the current salary as the dependent variable.

From the regression analysis the current salary of females can be predicted as:

  • Current Salary = 27641.5+0.8889*Starting salary

Further 70.19% of the variations in current salary of females can be predicted from their starting salary.

Males Salary

Calculations

b1, b0 Coefficients

0.8799

27952.7412

b1, b0 Standard Error

0.0599

2505.9337

R Square, Standard Error

0.6900

6843.6681

F, Residual df

215.9030

97.0000

Regression SS, Residual SS

10111986723.24

4543071979.31

 
 

Regression Statistics

Multiple R

0.8307

R Square

0.6900

Adjusted R Square

0.6868

Standard Error

6843.6681

Observations

99

 

Regression analysis is used to evaluate the current salary of males based on their starting salary.

From the regression analysis the current salary of males can be predicted as:

  • Current Salary = 27952.7+0.8799*Starting salary

Further 69.00% of the variations in current salary of males can be predicted from their starting salary.

Comparing the regression equation, it is seen that the basic salary of males is higher than females. Moreover, for one-unit increase in starting salary the increase in salary of females (0.8889) is higher than for males (0.8799).

Thus it is found that the salary increases for females is higher than males with the same starting salary. However, since the base salary of males is higher (27952.7) as compared to females (27641.5), thus the current salary for males would be higher.

Conclusion:

The present solution analysis the salaries of the employees of the organization. The initial analysis shows that the average salary of females is higher than males. However, the median salary of males is higher than females. Moreover, it is found that the average current salary of bot males and females is right skewed.

Even though the average current salary of females is higher than males, but the hypothesis tests that the average salary are equal.

It is found that the average current salary of both males and females varies across positions. In addition, there is variation in proportion of males and females across departments.

The investigation shows that the average increment in salary is left skewed. The average increment for genders is normally distributed.  Further, it is seen that the minimum average increment for females is more than males. It is also found that the maximum average increment for males is higher than females.

The current salary on the basis of the starting salary is higher for males than females.      


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