Australian Graduate Salary Trends & Projections

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AI Summary
This comparative study analyzes Australian graduate salary data from 1999 to 2015 across all graduates, computing, accounting, and social science disciplines. It utilizes linear regression models to project salaries for 2016, 2017, 2020, and 2025. The report highlights the increasing trend of graduate salaries in Australia and provides insights into salary variations across different fields.
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Running head: Comparative study and projection 1
A Comparative study and projection of Australian Graduate Salaries
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Comparative study and projection 2
Table of Contents
Executive Summary...........................................................................................................3
1. Purpose of report..............................................................................................................4
2. Findings...........................................................................................................................4
2.1 Analysis of findings...................................................................................................5
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Comparative study and projection 3
3. Conclusion.......................................................................................................................6
Appendix..............................................................................................................................8
Fig 1 - Comparison of salary trends in each field............................................................8
Fig 2 – Linear regression model for all graduates...........................................................8
Fig 3 – Linear regression model for accounting..............................................................9
Fig 4 – Linear regression model for computing..............................................................9
Fig 5 – Linear regression model for social science.......................................................10
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Comparative study and projection 4
Executive Summary
This report analyses the data of Australian graduate salaries for the period 1999 to 2015 and
presents a comparative study of the data for all graduates, computing graduates, accounting
graduates and social science graduates. This report gives a view of the trend in which Australian
graduate salaries are heading over the given time frame. This report also forecasts their salaries
for year 2016, 2017, 2020 and 2025.
Keywords: forecast, linear regression method, moving average, Australian Graduate
salaries
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Comparative study and projection 5
1. Purpose of report
This report is carried out to study the trend in Australian graduate salaries over the period
1999 to 2015. For the purpose of study data is obtained from the research reports named
GradStats for the years 1999 to 2015 from Graduate Careers Australia site. A summary of
preliminary data related to the destinations of Australian resident bachelor degree graduates is
given in GradStats (GradStats). From these reports data of graduate salaries were taken for all
graduates, computing graduates, accounting graduates and social science graduates. This data is
shown in the table in appendix. This report also forecasts their salaries for year 2016, 2017, 2020
and 2025.
2. Findings
Table in appendix shows the median annual starting salary for Australian resident new
bachelor degree graduates aged less than 25 and in their first full-time employment in Australia.
From the data it is clear that the salaries of the graduates in disciplines taken for study is on rise
over the years. Although different disciplines follow different pattern but altogether they are on
the rising side. For example for all graduates the salary rise is 74.2% from 1999 to 2015.
Similarly for accounting this rise is 72.4%, for computing 54.3% and for social science graduates
it is 67.9%. This rise and its pattern individually is shown in figure 2 to 5. Their comparison is
also shown in figure-1 which gives the relative position of salaries in different areas. This figure
can be divided into three time ranges namely 1999-2004, 2004-2009 and 2009-2015. From the
figure we can see that in first time frame the rise in salaries is nominal and comes out to be
20.7% for accounting, 8.6% for computing, 21.4% for social science and 22.6% for all graduates
salaries. In second time frame this rise is high and comes out to be 28.6% for accounting, 30.5%
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Comparative study and projection 6
for computing, 23.5% for social science and 26.3% for all graduates salaries. Lastly in the third
time frame the rise in salaries is least and comes out to be 12.5% for accounting, 10.0% for
computing, 12.7% for social science and 14.0% for all graduates salaries.
2.1 Analysis of findings
From the data collected and studied we can see that the trend of salaries over the given
time frame is rising. When this data is plotted as shown in figures 2 to 5 we can see that it
follows a close resemblance to a linear pattern. Thus while analyzing the data we will be
following the linear regression model. The individual plots for all graduates, computing,
accounting and social sciences are plotted in scattered form of graph and then their linear
regression trend line is plotted in excel as shown in figures 2 to 5. Since simple linear regression
model follows the equation
Y = mX + C
Hence from the plots we can get the values of m and C. these values comes out to be as given
below:-
1. For All Graduates -> m = 1.5029 and C = -2973.1
2. For Accounting -> m = 1.4363 and C = -2842.1
3. For Computing -> m = 1.3123 and C = -2588.8
4. For Social Science -> m = 1.2468 and C = -2462.8
Now once we have got the linear plot for individual fields we are in the position to calculate the
forecasted salary for each discipline for future years. In the table we have forecasted the salaries
for years 2016, 2017, 2020 and 2025.
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Comparative study and projection 7
3. Conclusion
As per the report the mean salary of all graduates in Australia is going to be increased.
Average mean salary is expected to be $56800 in 2016, $58300 in 2017, $62900 in 2020 and
$70400 in 2025.
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Comparative study and projection 8
4. References
GradStats. (n.d.). Retrieved from Graduate Careers Australia:
http://www.graduatecareers.com.au/research/researchreports/gradstats/
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Comparative study and projection 9
Appendix
Fig 1 - Comparison of salary trends in each field
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
0.0
20.0
40.0
60.0
Comparison of salary trends in each field
All Accounting Computer Science Social Sciences
Fig 2 – Linear regression model for all graduates
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
0.0
10.0
20.0
30.0
40.0
50.0
60.0
f(x) = 1.50294117647059 x − 2973.09117647059
All Graduates
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Comparative study and projection 10
Fig 3 – Linear regression model for accounting
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
0.0
10.0
20.0
30.0
40.0
50.0
60.0
f(x) = 1.43627450980392 x − 2842.07352941177
Accounting
Fig 4 – Linear regression model for computing
1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
0.0
10.0
20.0
30.0
40.0
50.0
60.0
f(x) = 1.31225490196078 x − 2588.77205882353
Computer Science
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