A Study of Salary and Occupation Relationship in Australia

Table of Contents
Introduction:....................................................................................................2
Descriptive Statistics:......................................................................................4
Inferential Statistics:........................................................................................7
Discussion & Conclusion................................................................................12
Introduction

a. The article is based on the analysis of salaries and occupation of different
gender. The data for the study has been provided by Australian Taxation
Office (ATO) for a particular location in Australia.
The requirement of the study is to know about the relationship between
salaries and occupation for different gender. So, consider the research
question of the study as, whether there is a significance difference between
the average salaries of different gender. To analysis a research question, the
data has been collected for a particular location in Australia.
b. The dataset 1 has been provided by Australian Taxation Office (ATO) for a
particular location in Australia which holds the taxation data. Thus, dataset 1
has been obtained from other source, so it can be consider as a secondary
data. The dataset 1 consists data of 1000 employees which have 4 variables
that are 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 shown below;
Gen
der
Occ_c
ode
Sw_
amt
Gift_
amt
Mal
e 9 3130
4 0
Fem
ale 0 0 27
Fem
ale 2 8693
4 0
Fem 4 2864 144

ale 9
Fem
ale 3 6962
0 0
c. The dataset 2 has been collected randomly by offline survey, the
researcher asked questions to working people about their gender, position
and the income amount. Thus dataset 2 is a primary data.
The dataset covers 100 values which is greater than 30, so the results from
the study will not be biased. The dataset have 3 variables that are Gender,
Occupation code, salary/wage amount. 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 bar 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
96
29
87
18
57
95
32
2
29
33
97
51
77
76
26
25
21
44
59
46
Male Female
The above bar plot indicates, Out of 1000, 77 male and 87 female employees
were professionals, 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