a.Give a brief introduction about the assignment, including your research question. Include a short summary of a related article with a proper citation.
b.Dataset 1: Give a short description about this dataset. Is this primary or secondary data? What types of variable(s) is involved? Display the first 5 cases of your dataset.
c.Dataset 2: Explain how you collect the data and discuss its limitation (e.g. whether your sample is biased). Is this primary or secondary data? What type of variable(s) is/are involved? You don’t need to display your data in this section.
a.Using suitable graphical display, describe the relationship between the variables Gender and Occ_code for Dataset 1. Make sure your graph shows the distribution of Gender for each Occ_code.
b.Using suitable graphical display, describe the relationship between the variables Gender and Sw_amt
c.Using suitable numerical summary, describe the relationship between the variables Gender and Sw_amt.
d.Using suitable graphical display, describe the relationship between the variables Sw_amt and Gift_amt.
a.List top 4 occupation based on median salary and find the proportion of the gender of those top 4 occupation.
b.Perform a suitable hypothesis test at a 5% level of significance to test whether the proportion of machinery operators and drivers who are male is more than 80%.
c.Perform a suitable hypothesis test at a 5% level of significance to test whether there is a difference in salary amount between gender.
d.Perform a suitable statistical analysis on dataset 2 (the one you collected) that will answer your research question.
Discussion & Conclusion
a.What can you conclude from your findings in the previous sections?
b.Give a suggestion for further research
a.The article is based on the study of relationship between the salaries of different gender in relation to the occupation of the taxation data of a particular location in Australia.
It is also need to the collection of data connecting the research question of business problem from a relative population and analysis of the collected data (dataset 2) using suitable statistical analysis. The business manager wants to know about the relationship between the salaries of different gender in relation to the occupation. So, the research question will be to know whether there is a significance difference between the average salary of male and female.
b.The dataset 1 holds the taxation data of a particular location in Australia which is provided by Australian Taxation office. So, the dataset is obtained for the other source which is Australian Taxation office, thus it is a secondary data. The dataset contains the data of 1000 employees which consists 4 variables as (Gender, Occupation code, salary/wage amount and the gift amount. The variable gender is divided into two categories as female and male, so the variables gender is measured into a nominal level of measurement. The variable occupation code indicates the occupation of the employees which is divided into 10 categories, so the variables occupation is measured into a nominal level of measurement. The variable salary/wage amount is the salary of the employees which contains numeric values, so it interval/ratio level of measurement and the gift amount indicates the gift or donation deductions which contains numeric values, so it an interval/ratio level of measurement.
The first five values of the dataset is shown below;
Gender 
Occ_code 
Sw_amt 
Gift_amt 
Female 
2 
32733 
0 
Female 
5 
13445 
0 
Female 
1 
50507 
109 
Male 
0 
0 
0 
Female 
9 
20489 
0 
c.The dataset 2 is collected by offline survey and asked to employees randomly about their gender, position and the income amount. So, the dataset is obtained by the survey, thus it is a primary data. The dataset contains 40 observations and collected randomly and also the sample size is greater than 30, so it can say that the collected data will be unbiased. The dataset contains the data of 40 employees which consists 3 variables as (Gender, Occupation code, salary/wage amount). The variable gender is divided into two categories as female and male, so the variables gender is measured into a nominal level of measurement. The variable occupation code indicates the occupation of the employees which is divided into 8 categories, so the variables occupation is measured into a nominal level of measurement. The variable salary/wage amount is the salary of the employees which contains numeric values, so it an interval/ratio level of measurement.
a.The bar graph for the relationship between variable Gender and the occupation is shown below:
The above bar plot indicates that, most of employees not listed their occupation otherwise it is not specified. Out of 1000, 81 male and 77 female employees were professionals, 86 male and 16 female employees were technicians ate trades workers, 26 male and 92 female employees were clerical and administrative workers, and 21 male and 44 female employees were sales workers.
Dataset 2
b.The pie chart for the relationship between variable Gender and the salary/Wage amount is shown below:
The male earns 68% of the total salary and male earns 32% of the total salary.
c.The numerical summary for the relationship between variable Gender and the salary/Wage amount is shown below:
Gender 
Average of Sw_amt 
Count of Sw_amt 
Max of Sw_amt 
StdDev of Sw_amt 
Sum of Sw_amt 
Female 
31768.51 
461 
308183 
32603.49 
14645283 
Male 
57830.74 
539 
839840 
67008.17 
31170769 
Grand Total 
45816.05 
1000 
839840 
55466.19 
45816052 
The total number of female employees is 461 and the male employees is 539. The average salary of a female employee is $31768.51 and for the male employee is $57830.74. The maximum salary of a female employee is $308183 and the maximum salary of a male employee is $839840. The, total salary of a female employee is $14645283 and the total salary of a male employee is $31170769.
d.The graphical summary for the relationship between variable Salary/Wage amount and Gift amount is shown below:
The salary wage for female employees is 31.97% and the gift wage for the female employees is 51.85%. The salary wage for male employees is 68.03% and the gift wage for the male employees is 48.15%
a.The top 4 occupation based on median salary and the proportion of the gender of those top 4 occupations is shown below:
Row Labels 
Female 
Male 
Grand Total 
Occupation not listed/ Occupation not specified 
9.40% 
11.80% 
21.20% 
Professionals 
7.70% 
8.10% 
15.80% 
Clerical and Administrative Workers 
9.20% 
2.60% 
11.80% 
Technicians and Trades Workers 
1.60% 
8.60% 
10.20% 
The top salary employees does not listed or not specified their Occupation, and the top salary is 21.20% of the total salary in which female earn 9.40% and male earn 11.80%. The Professionals get 15.80% of the total salary in which female earn 7.70% and male earn 8.10%. The Professionals get 15.80% of the total salary in which female earn 7.70% and male earn 8.10%. The Clerical and Administrative Workers get 11.80% of the total salary in which female earn 9.20% and male earn 2.60%. The Technicians and Trades Workers get 10.20% of the total salary in which female earn 1.60% and male earn 8.60%.
b.To test whether the proportion of machinery operators and drivers who are male is more than 80%, one sample Ztest will be used. The hypothesis of the test is given below:
The formula to calculate the value of the test statistic is given below:
The proportion of male the Machinery operators and drivers is about 93%. Now calculate the value of test statistic, the calculation are provided in Excel. The obtained results are shown below:
Z Test of Hypothesis for the Proportion 

Null Hypothesis p = 
0.8 
Level of Significance 
0.05 
Number of Items of Interest 
93 
Sample Size 
100 
Intermediate Calculations 

Sample Proportion 
0.93 
Standard Error 
0.0400 
Z Test Statistic 
3.2500 
UpperTail Test 

Upper Critical Value 
1.6449 
pValue 
0.0006 
Reject the null hypothesis 

c.According to the above results, the Pvalue of the test is less than 5% level of significance, so the null hypothesis of the test gets rejected. Thus, it can be concluded that the proportion of machinery operators and drivers who are male is more than 80%.
To test whether there is a difference in salary amount between gender, twosample ttest will be used. The hypothesis of the test is given below:
The difference between the sample variances is, (4490095016.9213/1062987395.6461 =4.22) which is greater than 1.5. So, the separate variance ttest will be used for analysis.
Now calculate the value of test statistic, the calculation is provided in Excel. The obtained results are shown below:
SeparateVariances tTest for the Difference Between Two Means 

Hypothesized Difference 
0 

Level of Significance 
0.05 

Female Salary 

Sample Size 
461 

Sample Mean 
31768.50976 

Sample Standard Deviation 
32603.4875 

Male Salary 

Sample Size 
539 

Sample Mean 
57830.74026 

Sample Standard Deviation 
67008.1713 

Numerator of Degrees of Freedom 
113129749452334.0000 

Denominator of Degrees of Freedom 
140546947310.5650 

Total Degrees of Freedom 
804.9250 

Degrees of Freedom 
804 

Standard Error 
3261.3260 

Difference in Sample Means 
26062.2305 

SeparateVariance t Test Statistic 
7.9913 

TwoTail Test 

Lower Critical Value 
1.9629 

Upper Critical Value 
1.9629 

pValue 
0.0000 
According to the above results, the Pvalue of the test is less than 5% level of significance, so the null hypothesis of the test gets rejected. Thus, it can be concluded that there is a difference in salary amount between gender.
d.To test whether there is a significance difference between the average salary of male and female, twosample ttest will be used. The hypothesis of the test is given below:
The difference between the sample variances is, (6068626974/2911806589 =2.08) which is greater than 1.5. So, the separate variance ttest will be used for analysis.
Now calculate the value of test statistic, the calculation is provided in Excel. The obtained results are shown below:
SeparateVariances t Test for the Difference Between Two Means 

Hypothesized Difference 
0 

Level of Significance 
0.05 

Female Salary 

Sample Size 
21 

Sample Mean 
59330.80952 

Sample Standard Deviation 
53961.1581 

Male Salary 

Sample Size 
19 

Sample Mean 
63553.68421 

Sample Standard Deviation 
77901.3926 

Numerator of Degrees of Freedom 
209817934130659000.0000 

Denominator of Degrees of Freedom 
6628920451792470.0000 

Total Degrees of Freedom 
31.6519 

Degrees of Freedom 
31 

Standard Error 
21402.3101 

Difference in Sample Means 
4222.8747 

SeparateVariance t Test Statistic 
0.1973 

TwoTail Test 

Lower Critical Value 
2.0395 

Upper Critical Value 
2.0395 

pValue 
0.8449 
According to the above results, the Pvalue of the test is less than 5% level of significance, so the null hypothesis of the test gets rejected. Thus, it can be concluded that there is a significance difference between the average salary of male and female.
Conclusion
The male earns 68% of the total salary and male earns 32% of the total salary. The total number of female employees is 461 and the male employees is 539. The average salary of a female employee is $31768.51 and for the male employee is $57830.74. The maximum salary of a female employee is $308183 and the maximum salary of a male employee is $839840. The, total salary of a female employee is $14645283 and the total salary of a male employee is $31170769.
The Professionals get 15.80% of the total salary in which female earn 7.70% and male earn 8.10%. The Professionals get 15.80% of the total salary in which female earn 7.70% and male earn 8.10%. The Clerical and Administrative Workers get 11.80% of the total salary in which female earn 9.20% and male earn 2.60%. The Technicians and Trades Workers get 10.20% of the total salary in which female earn 1.60% and male earn 8.60%.
The study from the provided data from Australian Taxation Office (ATO) indicates that the proportion of machinery operators and drivers who are male is more than 80%, and there is a difference in salary amount between gender.
The study from the sample survey of 40 employees indicates that there is a significance difference between the average salary of male and female.
Most of employees not listed their occupation otherwise it is not specified which is 21.20% of the total salary. So, the Australian Taxation Office (ATO) should collect the data for each occupation which will be helpful in the further study of salary analysis.
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