Gender Inequality in Australian Society

This assignment examines the issue of gender inequality within Australian society. It analyzes data related to individual income and highest level of education, comparing figures for men and women across various categories. The analysis suggests that women face disadvantages in terms of earning potential and are less represented in certain fields like trade apprenticeships. The document concludes by highlighting the prioritization of men over women in socioeconomic status within Australia.

Running Head: SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
SOC5QSR Quantitative Skills for Social Research
Name of the Student
Name of the University
Author Note

1SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
Part 1
The first variable considered here is State. The variable indicates in which state the
individual resides in. For the variables how many years of education and age, mean is the most
appropriate measure of central tendency. This measure gives the average number of years of
education and the average age of the individuals. The variable State is a categorical variable.
Thus, no measure of descriptive statistics can be appropriate in measuring this variable.
Most people have studied for 10 years, 12 years and 15 years. Most of the people are
from New South Wales and most of the people fall in the age group of 51-60 years. These data
can be clearly visible from the histograms given below. The variables in this part are all discrete
variables. The grouping of ages is also taken in such a way that it is a discrete variable. Thus, the
data can be represented most appropriately by a bar graph. Bar graph is the most appropriate
chart to represent discrete data.
Statistics
R: How many years of
education have you
completed?
State R: Age (10yr categories)
N Valid 2705 2775 2737
Missing 76 6 44
Mean 13.57 2.58 3.52
Median 14.00 2.00 4.00
Mode 12 1 4
Std. Deviation 3.640 1.597 1.632
Variance 13.246 2.551 2.663
Skewness .330 1.011 .131
Std. Error of Skewness .047 .046 .047
Kurtosis 1.389 .441 -.819
Std. Error of Kurtosis .094 .093 .094
Range 40 7 6

2SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
Minimum 0 1 1
Maximum 40 8 7
Percentiles
25 11.00 1.00 2.00
50 14.00 2.00 4.00
75 16.00 3.00 5.00
R: How many years of education have you completed?
Frequency Percent Valid Percent Cumulative Percent
Valid 0 2 .1 .1 .1
2 6 .2 .2 .3
3 4 .1 .1 .4
4 2 .1 .1 .5
5 10 .4 .4 .9
6 23 .8 .9 1.7
7 36 1.3 1.3 3.1
8 88 3.2 3.3 6.3
9 117 4.2 4.3 10.6
10 309 11.1 11.4 22.1
11 208 7.5 7.7 29.8
12 322 11.6 11.9 41.7
13 210 7.6 7.8 49.4
14 263 9.5 9.7 59.1
15 304 10.9 11.2 70.4
16 257 9.2 9.5 79.9
17 194 7.0 7.2 87.1
18 141 5.1 5.2 92.3
19 63 2.3 2.3 94.6
20 76 2.7 2.8 97.4
21 20 .7 .7 98.2
22 23 .8 .9 99.0
23 11 .4 .4 99.4
24 2 .1 .1 99.5
25 5 .2 .2 99.7
26 3 .1 .1 99.8
27 1 .0 .0 99.8

3SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
28 3 .1 .1 99.9
30 1 .0 .0 100.0
40 1 .0 .0 100.0
Total 2705 97.3 100.0
Missing Missing 76 2.7
Total 2781 100.0
State
Frequency Percent Valid Percent Cumulative Percent
Valid
New South Wales 898 32.3 32.4 32.4
Victoria 687 24.7 24.8 57.1
Queensland 538 19.3 19.4 76.5
South Australia 235 8.5 8.5 85.0
Western Australia 267 9.6 9.6 94.6
Tasmania 81 2.9 2.9 97.5
ACT 51 1.8 1.8 99.4
Northern Territory 18 .6 .6 100.0
Total 2775 99.8 100.0
Missing Missing 6 .2
Total 2781 100.0
R: Age (10yr categories)
Frequency Percent Valid Percent Cumulative Percent
Valid
18-30 376 13.5 13.7 13.7
31-40 419 15.1 15.3 29.0
41-50 568 20.4 20.8 49.8
51-60 589 21.2 21.5 71.3
61-70 428 15.4 15.6 87.0
71-80 272 9.8 9.9 96.9
Over 80 85 3.1 3.1 100.0
Total 2737 98.4 100.0
Missing Missing 44 1.6
Total 2781 100.0

4SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH

5SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH

6SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
Part 2
In this part the variables were recoded to a new variable by eliminating the missing
values, the unknown values and the responses not known. Including these responses will give
vague results of the analysis as these responses have no effect with the analysis. Thus, the values
coded to them will give wrong interpretation.
In this part, it can be seen that the p-values of the Chi-Square statistics for education in
predicting attitude towards government’s performance in controlling crime are less than 0.05
(The level of significance). Thus, it can be said that there is no association between the variables
for which the cross tabulation has been conducted.
B8d Recoded * M5 Recoded Crosstabulation
Count
M5 Recoded Total
1.00 2.00 3.00 4.00 5.00
B8d Recoded
1.00 14 7 11 9 2 43
2.00 233 114 219 140 105 811
3.00 310 166 294 141 86 997
4.00 188 106 165 60 45 564
5.00 53 39 50 19 20 181
Total 798 432 739 369 258 2596
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 37.461a 16 .002
Likelihood Ratio 37.388 16 .002
Linear-by-Linear Association 11.927 1 .001
N of Valid Cases 2596
a. 1 cells (4.0%) have expected count less than 5. The minimum expected count is 4.27.

7SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
L2 Recoded * M7 Recoded Crosstabulation
Count
M7 Recoded Total
1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00
L2
Recoded
1.00 7 4 4 3 5 3 2 3 31
2.00 11 19 3 4 4 3 0 1 45
3.00 75 109 23 21 35 21 7 6 297
4.00 114 159 67 45 102 46 16 33 582
5.00 80 97 82 46 98 41 26 41 511
6.00 58 91 93 63 108 50 32 54 549
7.00 10 17 34 24 34 18 14 37 188
8.00 3 4 11 13 10 8 8 10 67
9.00 0 2 5 7 4 0 0 5 23
10.00 1 1 3 0 3 1 1 4 14
Total 359 503 325 226 403 191 106 194 2307
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 293.463a 63 .000
Likelihood Ratio 300.098 63 .000
Linear-by-Linear Association 151.438 1 .000
N of Valid Cases 2307
a. 26 cells (32.5%) have expected count less than 5. The minimum expected count is .64.
In this part, it can be seen that the p-values of the Chi-Square statistics for occupation in
predicting identification of social position are less than 0.05 (The level of significance). Thus, it
can be said that there is no association between the variables for which the cross tabulation has
been conducted.

8SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
B23 Recoded * M15 Recoded Crosstabulation
Count
M15 Recoded Total
1.00 2.00
B23 Recoded
1.00 196 91 287
2.00 450 157 607
3.00 542 148 690
4.00 512 122 634
5.00 340 58 398
Total 2040 576 2616
Chi-Square Tests
Value df Asymp. Sig. (2-sided)
Pearson Chi-Square 36.746a 4 .000
Likelihood Ratio 36.596 4 .000
Linear-by-Linear Association 35.722 1 .000
N of Valid Cases 2616
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 63.19.
In this part, it can be seen that the p-values of the Chi-Square statistics for birth place in
predicting size of social contact are less than 0.05 (The level of significance). Thus, it can be said
that there is no association between the variables for which the cross tabulation has been
conducted.

9SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
Part 3
To test whether there is any difference between the incomes of males and females,
independent sample t-test has been done in SPSS. From the results, it can be seen that the p-
value or the Sig (2-tailed) value is 0.000, which is less than the level of significance (0.05). Thus,
there is significant difference between the individual annual incomes of males and females in the
society. Moreover, it is clear from the Group statistics table that the income of males is
comparatively higher than that of females. Thus, there is a socio economic difference in the
income of the individuals with respect to gender.
Group Statistics
R: Gender N Mean Std. Deviation Std. Error Mean
Individual income - gross
annual (4 categories)
Female 1311 2.06 .932 .026
Male 1220 2.65 1.006 .029
Independent Samples Test for Individual Income with respect to gender.
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95%
Confidence
Interval of the
Difference
Lower Upper
Individual
income -
gross annual
(4
categories)
Equal
variances
assumed
23.842 .000 -
15.320 2529 .000 -.590 .039 -.666 -.515
Equal
variances not
assumed
-
15.278 2474.476 .000 -.590 .039 -.666 -.515
To test whether there is any difference in the highest degree of education perused by a
male and a female, again, independent sample t-test has been conducted. According to the results

10SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
of the t-test, it can be seen that the p-value is 0.342, which is greater than the level of
significance. Thus, there is no significant difference in the highest degree of education perused
by a male and a female.
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper
R: Highest
level of
education
completed
since leaving
school
Equal
variances
assumed
10.744 .001 .950 2696 .342 .048 .051 -.052 .149
Equal
variances not
assumed
.953 2690.430 .341 .048 .051 -.051 .148
Thus, it can be said the Australian society still considers women downtrodden and do not
consider them fit for work. This is why the women earn less than the men even though they have
almost the same level of qualification.
The variables that have been considered to affect the socio economic status of the people
are highest level of education and individual income. From the cross tabulation table of
Individual income and gender, it can be clearly seen that more women earn the lesser annual
income than men. Men are more likely to earn the higher annual incomes. Thus, men are given
much more priority in the in the country than the women.

11SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
Individual income - gross annual (4 categories) * R: Gender Crosstabulation
Count
R: Gender Total
Female Male
Individual income - gross annual
(4 categories)
$0 to $15,599 per annum 446 216 662
$15,600 to $36,399 per annum 433 261 694
$36,400 to $77,999 per annum 344 481 825
$78,000 and over per annum 88 262 350
Total 1311 1220 2531
Again, from the cross tabulation table for the highest level of education, it can be seen
that women are advance than men in most of the cases. Only in trade or apprenticeship, more
men have studied than women. Thus, any trade related studies are perused more by men than
women. Women just get high education. They do not get the proper education that is necessary
work. Thus, this explains their low annual income than men. Thus, these indicate that men are
more prioritized than women in the socio economic status.

12SOC5QSR QUANTITATIVE SKILLS FOR SOCIAL RESEARCH
R: Highest level of education (5 categories) * R: Gender Crosstabulation
Count
R: Gender Total
Female Male
R: Highest level of education (5
categories)
Less than Year 12 351 219 570
Year 12 164 128 292
Trade/Apprenticeship 88 359 447
Certificate/Diploma 481 284 765
Bachelor degree and above 349 302 651
Total 1433 1292 2725