Gender Differences in Salary - PDF
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Table of Contents
Introduction:....................................................................................................2
Descriptive Statistics:......................................................................................5
Inferential Statistics:........................................................................................8
Discussion & Conclusion:...............................................................................10
Introduction:....................................................................................................2
Descriptive Statistics:......................................................................................5
Inferential Statistics:........................................................................................8
Discussion & Conclusion:...............................................................................10
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Introduction:
a. The article is concern to do the analysis of salaries and occupation of
different gender. The data is taken from Australian Taxation Office (ATO) for
a particular location in Australia.
The necessity of the study is to distinguish about the relationship between
salaries and occupation for different gender. This, the research question of
the study can be considered as, whether there is a significance difference
between the average salaries of male and female employees. To analyze the
research question, the data collected for a particular location in Australia.
b. The dataset 1 is a taxation data provided by Australian Taxation Office
(ATO) for a particular location in Australia. So, dataset 1 is a secondary data
because it is obtained from another source. The dataset 1 have data for
1000 employees which consists information about Gender, Occupation code,
salary/wage amount and the gift amount. The variable gender has divided
into two categories as female and male, so it is a nominal level variable. The
variable occupation code specifies the occupation of the employees which
has divided into 10 categories, so it is a nominal level variable. The variable
salary/wage amount indicates the salary of the employees, so it interval/ratio
level variable. The gift amount indicates the gift or donation deductions, so it
interval/ratio level variable.
The first five values of the dataset 1 is,
Gen
der
Occ_c
ode
Sw_a
mt
Gift_
amt
Male 9 3130
4
0
Fem
ale
0 0 27
Fem
ale
2 8693
4
0
a. The article is concern to do the analysis of salaries and occupation of
different gender. The data is taken from Australian Taxation Office (ATO) for
a particular location in Australia.
The necessity of the study is to distinguish about the relationship between
salaries and occupation for different gender. This, the research question of
the study can be considered as, whether there is a significance difference
between the average salaries of male and female employees. To analyze the
research question, the data collected for a particular location in Australia.
b. The dataset 1 is a taxation data provided by Australian Taxation Office
(ATO) for a particular location in Australia. So, dataset 1 is a secondary data
because it is obtained from another source. The dataset 1 have data for
1000 employees which consists information about Gender, Occupation code,
salary/wage amount and the gift amount. The variable gender has divided
into two categories as female and male, so it is a nominal level variable. The
variable occupation code specifies the occupation of the employees which
has divided into 10 categories, so it is a nominal level variable. The variable
salary/wage amount indicates the salary of the employees, so it interval/ratio
level variable. The gift amount indicates the gift or donation deductions, so it
interval/ratio level variable.
The first five values of the dataset 1 is,
Gen
der
Occ_c
ode
Sw_a
mt
Gift_
amt
Male 9 3130
4
0
Fem
ale
0 0 27
Fem
ale
2 8693
4
0

Fem
ale
4 2864
9
144
Fem
ale
3 6962
0
0
c. The dataset 2 collected by offline survey by asking questions to working
employees about their gender, position and the salary/wage amount, so it is
a primary data.
The dataset covers 50 values which are large enough to provide unbiased of
the study. The variable gender has been divided into two categories as
female and male, so it is a nominal level of measurement. The variable
occupation code indicates the occupation of the employees which has been
divided into 10 categories, so it is a nominal level of measurement. The
variable salary/wage amount indicates the salary of the employees, so it
interval/ratio level of measurement.
ale
4 2864
9
144
Fem
ale
3 6962
0
0
c. The dataset 2 collected by offline survey by asking questions to working
employees about their gender, position and the salary/wage amount, so it is
a primary data.
The dataset covers 50 values which are large enough to provide unbiased of
the study. The variable gender has been divided into two categories as
female and male, so it is a nominal level of measurement. The variable
occupation code indicates the occupation of the employees which has been
divided into 10 categories, so it is a nominal level of measurement. The
variable salary/wage amount indicates the salary of the employees, so it
interval/ratio level of measurement.

Descriptive Statistics:
a. The graph for the relationship between variable Gender and the
occupation is shown below:
Occupation not listed/ Occupation not specified
Managers
Professionals
Technicians and Trades Workers
Community and Personal Service Workers
Clerical and Administrative Workers
Sales workers
Machinery operators and drivers
Labourers
Consultants, apprentices and type not specified or
not listed
0 20 40 60 80 100 120
Relationship between variable Gender and the occupation
Male Female
Out of 1000, 21 male and 32 female employees were sales workers, 76 male
and 18 female employees were technicians ate trades workers, 97 male and
96 female employees not listed their occupation otherwise it is not specified,
25 male and 95 female were clerical and administrative workers, 59 male
a. The graph for the relationship between variable Gender and the
occupation is shown below:
Occupation not listed/ Occupation not specified
Managers
Professionals
Technicians and Trades Workers
Community and Personal Service Workers
Clerical and Administrative Workers
Sales workers
Machinery operators and drivers
Labourers
Consultants, apprentices and type not specified or
not listed
0 20 40 60 80 100 120
Relationship between variable Gender and the occupation
Male Female
Out of 1000, 21 male and 32 female employees were sales workers, 76 male
and 18 female employees were technicians ate trades workers, 97 male and
96 female employees not listed their occupation otherwise it is not specified,
25 male and 95 female were clerical and administrative workers, 59 male
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and 29 female were laborers, 26 male and 57 female were community and
personal service workers and 77 male and 87 female employees were
professionals.
b. The graphical relationship between variable Gender and the salary/Wage
amount is shown below:
Female
39%
Male
61%
Relationship between variable Gender and the salary/Wage amount
Female
Male
The female earns about 39% of the total salary and male earns is about 61%
of the total salary.
personal service workers and 77 male and 87 female employees were
professionals.
b. The graphical relationship between variable Gender and the salary/Wage
amount is shown below:
Female
39%
Male
61%
Relationship between variable Gender and the salary/Wage amount
Female
Male
The female earns about 39% of the total salary and male earns is about 61%
of the total salary.

c. The numerical summary for the relationship between variable Gender
and the salary/Wage amount is shown below:
Row
Labels
Average
of
Sw_amt
Max of
Sw_amt3
Count of
Sw_amt2
StdDev of
Sw_amt4
Sum of
Sw_amt
Female 33841.72 308183 478 33428.35 1617634
1
Male 48181.46 308183 522 46863.41 2515072
1
Grand
total
41327.06
2
308183 1000 41596.550
31
413270
62
The number of female employees is 478 and male employees is 522. The
average salary of 478 female employees is about $33841.7 and the average
salary of 522 male employees is $48181.46. The maximum salary of a
female employee is $308183 and the maximum salary of a male employee is
$308183. The total salary of female employees is $16176341 and the total
salary of male employees is $25150721.
d. The graphical summary for the relationship between variable Salary/Wage
amount and Gift amount is shown below:
and the salary/Wage amount is shown below:
Row
Labels
Average
of
Sw_amt
Max of
Sw_amt3
Count of
Sw_amt2
StdDev of
Sw_amt4
Sum of
Sw_amt
Female 33841.72 308183 478 33428.35 1617634
1
Male 48181.46 308183 522 46863.41 2515072
1
Grand
total
41327.06
2
308183 1000 41596.550
31
413270
62
The number of female employees is 478 and male employees is 522. The
average salary of 478 female employees is about $33841.7 and the average
salary of 522 male employees is $48181.46. The maximum salary of a
female employee is $308183 and the maximum salary of a male employee is
$308183. The total salary of female employees is $16176341 and the total
salary of male employees is $25150721.
d. The graphical summary for the relationship between variable Salary/Wage
amount and Gift amount is shown below:

Occupation not listed/ Occupation not specified
Managers
Professionals
Technicians and Trades Workers
Community and Personal Service Workers
Clerical and Administrative Workers
Sales workers
Machinery operators and drivers
Labourers
Consultants, apprentices and type not specified or
not listed
0 2000000 4000000 6000000 8000000 10000000 12000000
0
5576177
10648470
5441332
3038103
5640000
1629615
2712048
3146829
3494488
166674
9705
31058
5081
5480
10447
1381
1523
11305
5582
Relationship between variable Salary/Wage amount and Gift amount
Sum of Sw_amt Sum of Gift_amt
For Consultants, apprentices and type not specified or not listed, the sum of
gift amount is about $5582 and sum of salary and wage amount is about
$3494488. For Professionals, the sum of gift amount is about $31058 and
sum of salary and wage amount is about $10648470. For Machinery
operators and drivers, the sum of gift amount is about $1523 and sum of
salary and wage amount is about $2712048. For laborer, the sum of gift
amount is about $11305 and sum of salary and wage amount is about
$3146829.
Inferential Statistics:
a. The Professionals get 16.40% of the total salary in which female earns
8.70% and male earns 7.70%. The Clerical and Administrative Workers get
12% of the total salary in which female earns 9.50% and male earn 2.50%.
The Technicians and Trades Workers get 9.40% of the total salary in which
female earn 1.80% and male earn 7.60%. The top salary employees does not
Managers
Professionals
Technicians and Trades Workers
Community and Personal Service Workers
Clerical and Administrative Workers
Sales workers
Machinery operators and drivers
Labourers
Consultants, apprentices and type not specified or
not listed
0 2000000 4000000 6000000 8000000 10000000 12000000
0
5576177
10648470
5441332
3038103
5640000
1629615
2712048
3146829
3494488
166674
9705
31058
5081
5480
10447
1381
1523
11305
5582
Relationship between variable Salary/Wage amount and Gift amount
Sum of Sw_amt Sum of Gift_amt
For Consultants, apprentices and type not specified or not listed, the sum of
gift amount is about $5582 and sum of salary and wage amount is about
$3494488. For Professionals, the sum of gift amount is about $31058 and
sum of salary and wage amount is about $10648470. For Machinery
operators and drivers, the sum of gift amount is about $1523 and sum of
salary and wage amount is about $2712048. For laborer, the sum of gift
amount is about $11305 and sum of salary and wage amount is about
$3146829.
Inferential Statistics:
a. The Professionals get 16.40% of the total salary in which female earns
8.70% and male earns 7.70%. The Clerical and Administrative Workers get
12% of the total salary in which female earns 9.50% and male earn 2.50%.
The Technicians and Trades Workers get 9.40% of the total salary in which
female earn 1.80% and male earn 7.60%. The top salary employees does not
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listed or not specified their Occupation, and the top salary is 19.30% of the
total salary in which female earns 9.60% and male earn 9.70%. The results
of overall salary percentage for gender corresponding to each occupation is
shown below:
Occupation Fema
le
Male Total
Occupation not listed/ Occupation not
specified
9.60
%
9.70% 19.30
%
Managers 2.90
%
5.10% 8.00%
Professionals 8.70
%
7.70% 16.40
%
Technicians and Trades Workers 1.80
%
7.60% 9.40%
Community and Personal Service Workers 5.70
%
2.60% 8.30%
Clerical and Administrative Workers 9.50
%
2.50% 12.00
%
Sales workers 3.20
%
2.10% 5.30%
Machinery operators and drivers 0.20
%
4.40% 4.60%
Laborer’s 2.90
%
5.90% 8.80%
Consultants, apprentices and type not specified
or not listed
3.30
%
4.60% 7.90%
Grand Total 47.80
%
52.20
%
100.00
%
total salary in which female earns 9.60% and male earn 9.70%. The results
of overall salary percentage for gender corresponding to each occupation is
shown below:
Occupation Fema
le
Male Total
Occupation not listed/ Occupation not
specified
9.60
%
9.70% 19.30
%
Managers 2.90
%
5.10% 8.00%
Professionals 8.70
%
7.70% 16.40
%
Technicians and Trades Workers 1.80
%
7.60% 9.40%
Community and Personal Service Workers 5.70
%
2.60% 8.30%
Clerical and Administrative Workers 9.50
%
2.50% 12.00
%
Sales workers 3.20
%
2.10% 5.30%
Machinery operators and drivers 0.20
%
4.40% 4.60%
Laborer’s 2.90
%
5.90% 8.80%
Consultants, apprentices and type not specified
or not listed
3.30
%
4.60% 7.90%
Grand Total 47.80
%
52.20
%
100.00
%

b. The one sample Z-test will be used to test whether the proportion of
machinery operators and drivers who are male is more than 80%, the
hypothesis to test the claim can be defined as:
The null hypothesis is . And, the alternative hypothesis .
The proportion of male the Machinery operators and drivers is about 96%.
The calculations are done in excel, the calculated value of the Z-test statistic
is 4.00 and the corresponding P-value for the upper tailed test is 0.000. The
P-value of the test is less than 5% level of significance, so the null hypothesis
of the test gets rejected.
Hence, the proportion of machinery operators and drivers who are male is
more than 80%.
c. Two-sample t-test will be used to test whether there is a difference in
salary amount between gender. The hypothesis can be defined as,
The null hypothesis is that the mean salary of male and female is equal.
And, the alternative hypothesis is the mean salary of male and female is
different.
The ratio of the variance of male sample and female sample is greater than
1.5. So, the independent sample t-test will be useful. The calculations are
done in excel, the value of the test statistic is 5.60 and the corresponding P-
value of the two-tailed test is 0.000. The P-value of the test is less than 5%
level of significance, so the null hypothesis of the test gets rejected.
Hence, salary of male and female differ significantly.
d. Two-sample t-test will be used to test whether there is a difference in
salary amount between gender. The hypothesis can be defined as,
machinery operators and drivers who are male is more than 80%, the
hypothesis to test the claim can be defined as:
The null hypothesis is . And, the alternative hypothesis .
The proportion of male the Machinery operators and drivers is about 96%.
The calculations are done in excel, the calculated value of the Z-test statistic
is 4.00 and the corresponding P-value for the upper tailed test is 0.000. The
P-value of the test is less than 5% level of significance, so the null hypothesis
of the test gets rejected.
Hence, the proportion of machinery operators and drivers who are male is
more than 80%.
c. Two-sample t-test will be used to test whether there is a difference in
salary amount between gender. The hypothesis can be defined as,
The null hypothesis is that the mean salary of male and female is equal.
And, the alternative hypothesis is the mean salary of male and female is
different.
The ratio of the variance of male sample and female sample is greater than
1.5. So, the independent sample t-test will be useful. The calculations are
done in excel, the value of the test statistic is 5.60 and the corresponding P-
value of the two-tailed test is 0.000. The P-value of the test is less than 5%
level of significance, so the null hypothesis of the test gets rejected.
Hence, salary of male and female differ significantly.
d. Two-sample t-test will be used to test whether there is a difference in
salary amount between gender. The hypothesis can be defined as,

The null hypothesis is that the mean salary of male and female is equal.
And, the alternative hypothesis is the mean salary of male and female is
different.
The ratio of the variance of male sample and female sample is greater than
1.5. So, the independent sample t-test will be useful. The calculations are
done in excel, the value of the test statistic is 0.4391 and the corresponding
P-value of the two-tailed test is 0.664. The P-value of the test is greater than
5% level of significance, so the null hypothesis of the test does not gets
rejected.
Hence, salary of male and female not differ significantly.
Discussion & Conclusion:
a. Out of 1000, 21 male and 32 female employees were sales workers, 76
male and 18 female employees were technicians ate trades workers, 97
male and 96 female employees not listed their occupation otherwise it is not
specified, 25 male and 95 female were clerical and administrative workers,
59 male and 29 female were laborers, 26 male and 57 female were
community and personal service workers and 77 male and 87 female
employees were professionals.
The female earns about 39% of the total salary and male earns is about 61%
of the total salary.
The number of female employees is 478 and male employees is 522. The
average salary of 478 female employees is about $33841.7 and the average
salary of 522 male employees is $48181.46. The maximum salary of a
female employee is $308183 and the maximum salary of a male employee is
$308183. The total salary of female employees is $16176341 and the total
salary of male employees is $25150721.
And, the alternative hypothesis is the mean salary of male and female is
different.
The ratio of the variance of male sample and female sample is greater than
1.5. So, the independent sample t-test will be useful. The calculations are
done in excel, the value of the test statistic is 0.4391 and the corresponding
P-value of the two-tailed test is 0.664. The P-value of the test is greater than
5% level of significance, so the null hypothesis of the test does not gets
rejected.
Hence, salary of male and female not differ significantly.
Discussion & Conclusion:
a. Out of 1000, 21 male and 32 female employees were sales workers, 76
male and 18 female employees were technicians ate trades workers, 97
male and 96 female employees not listed their occupation otherwise it is not
specified, 25 male and 95 female were clerical and administrative workers,
59 male and 29 female were laborers, 26 male and 57 female were
community and personal service workers and 77 male and 87 female
employees were professionals.
The female earns about 39% of the total salary and male earns is about 61%
of the total salary.
The number of female employees is 478 and male employees is 522. The
average salary of 478 female employees is about $33841.7 and the average
salary of 522 male employees is $48181.46. The maximum salary of a
female employee is $308183 and the maximum salary of a male employee is
$308183. The total salary of female employees is $16176341 and the total
salary of male employees is $25150721.
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For Consultants, apprentices and type not specified or not listed, the sum of
gift amount is about $5582 and sum of salary and wage amount is about
$3494488. For Professionals, the sum of gift amount is about $31058 and
sum of salary and wage amount is about $10648470. For Machinery
operators and drivers, the sum of gift amount is about $1523 and sum of
salary and wage amount is about $2712048. For laborer, the sum of gift
amount is about $11305 and sum of salary and wage amount is about
$3146829.
The Professionals get 16.40% of the total salary in which female earns 8.70%
and male earns 7.70%. The Clerical and Administrative Workers get 12% of
the total salary in which female earns 9.50% and male earn 2.50%. The
Technicians and Trades Workers get 9.40% of the total salary in which
female earn 1.80% and male earn 7.60%. The top salary employees do not
list or not specified their Occupation, and the top salary is 19.30% of the
total salary in which female earns 9.60% and male earn 9.70%. The results
are shown below:
The proportion of male the Machinery operators and drivers is about 96%,
the proportion of machinery operators and drivers who are male is more than
80%.
The salary of male and female differ significantly in population and the salary
of male and female not differ significantly in sample.
b. The result of population and sample is different, so the study is not
providing accurate results. So, the data provided by the Australian taxation
office may not be accurate and may be old. So, the researcher should do the
analysis for the current data.
gift amount is about $5582 and sum of salary and wage amount is about
$3494488. For Professionals, the sum of gift amount is about $31058 and
sum of salary and wage amount is about $10648470. For Machinery
operators and drivers, the sum of gift amount is about $1523 and sum of
salary and wage amount is about $2712048. For laborer, the sum of gift
amount is about $11305 and sum of salary and wage amount is about
$3146829.
The Professionals get 16.40% of the total salary in which female earns 8.70%
and male earns 7.70%. The Clerical and Administrative Workers get 12% of
the total salary in which female earns 9.50% and male earn 2.50%. The
Technicians and Trades Workers get 9.40% of the total salary in which
female earn 1.80% and male earn 7.60%. The top salary employees do not
list or not specified their Occupation, and the top salary is 19.30% of the
total salary in which female earns 9.60% and male earn 9.70%. The results
are shown below:
The proportion of male the Machinery operators and drivers is about 96%,
the proportion of machinery operators and drivers who are male is more than
80%.
The salary of male and female differ significantly in population and the salary
of male and female not differ significantly in sample.
b. The result of population and sample is different, so the study is not
providing accurate results. So, the data provided by the Australian taxation
office may not be accurate and may be old. So, the researcher should do the
analysis for the current data.
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