Data Analysis: Descriptive Statistics and Tests for Mean Differences

This report presents descriptive statistics and tests for mean differences in aggression, thrill seeking, and risk acceptance scores by gender, metropolitan background status, study mode, and RTA follow-up survey. The report includes tables and interpretations of the results.

Data analysis 1
Student Name:
Student number:
Lecturer:

Data analysis 2
Question one
a. Age descriptive statistics
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
AGE 38681 16 59 20.50 4.889
Valid N (listwise) 38681
Table 1
It can be observed from the table above that the mean age for the participants was 20.5. The
youngest participant was 16 years old while the oldest participant was 59 years old.
b. Frequency for new age category
Statistics
Age category
N Valid 38681
Missing 0
Table 2
Age category
Frequency Percent Valid Percent Cumulative
Percent
Valid
18 years 11881 30.7 30.7 30.7
19 - 21 years 11666 30.2 30.2 60.9
22 - 25 years 5494 14.2 14.2 75.1
26 or more 3755 9.7 9.7 84.8
system missing 5885 15.2 15.2 100.0
Total 38681 100.0 100.0
Table 3
The table above table shows the frequency of age groups. Participants who were 18 years old
were 11,881 representing 30.7%. This was followed closely by those within the age of 19 to 21
years. They were 11,666 representing 30.2%. Those who were 26 years old and above were
3,755, representing 9.7% of the total.

Data analysis 3
Question two
Descriptive statistics for the demographics
Age descriptive statistics
Descriptive Statistics
N Sum Mean
AGE 38681 792845 20.50
Valid N (listwise) 38681
Table 4
The mean age of the participants was 20.5 while the sum total of their age was 792,845 years.
State descriptive
STATE
Frequency Percent Valid Percent Cumulative
Percent
Valid
NSW 15860 41.0 41.0 41.0
Victoria 13571 35.1 35.1 76.1
Queensland 7528 19.5 19.5 95.5
ACT 1722 4.5 4.5 100.0
Total 38681 100.0 100.0
Table 5
From the table above, it can be observed that 41% of the participants come from NSW, 35.1%
come from Victoria, and 19.5% come from Queensland while the minority of the participants
(4.5%) comes from ACT.

Data analysis 4
Gender descriptive
GENDER
Frequency Percent Valid Percent Cumulative
Percent
Valid
Male 10449 27.0 27.0 27.0
Female 28232 73.0 73.0 100.0
Total 38681 100.0 100.0
Table 6
It can be observed that majority of the participants were females. They were 28,232 in number
and represented 73%. The rest were females who were 10,449 representing 27%.
Living arrangement descriptive
LIVING_ARRANGE
Frequency Percent Valid Percent Cumulative
Percent
Valid
At home 20840 53.9 53.9 53.9
College/student
accommodation
6850 17.7 17.7 71.6
Independently 10991 28.4 28.4 100.0
Total 38681 100.0 100.0
Table 7
The table above shows the how participants are accommodated. It can be observed that 53.9%
(20,840) were being accommodated from their homes. 17.7% (6,850) were accommodated at the
college while 28.4% (10,991) had their own independent accommodation.

Data analysis 5
Faculty descriptive
FACULTY
Frequency Percent Valid Percent Cumulative
Percent
Valid
Arts and Sciences 9004 23.3 23.3 23.3
Education 15038 38.9 38.9 62.2
Health Sciences 11729 30.3 30.3 92.5
Theology and Philosophy 588 1.5 1.5 94.0
Business 2322 6.0 6.0 100.0
Total 38681 100.0 100.0
Table 8
The table above shows the distribution of the student participants based on their faculties.
Majority of them came from the faculty of education (15,038) representing 38.9%. This is
followed by students from the faculty of health sciences (11,729) who represented 30.3%. The
least number of students came from the faculty of theology and philosophy. They were 588
representing 1.5%.
Degree type descriptive
DEGREE_TYPE
Frequency Percent Valid Percent Cumulative
Percent
Valid
Single 34620 89.5 89.5 89.5
Double 4061 10.5 10.5 100.0
Total 38681 100.0 100.0
Table 9
The table above shows distribution of participants by the type of their degrees. It can be observed
that 89.5% were pursuing single degrees while 10.5% were pursuing double degrees.

Data analysis 6
Metro descriptive
METRO
Frequency Percent Valid Percent Cumulative
Percent
Valid
Metro 27223 70.4 84.4 84.4
Non-metro 5015 13.0 15.6 100.0
Total 32238 83.3 100.0
Missing System 6443 16.7
Total 38681 100.0
Table 10
The table above shows the location of origin of the students. It can be observed that majority of
them came from metropolitan areas (70.4%) while 13% came from non-metropolitan areas.
Study mode descriptive
STUDY_MODE
Frequency Percent Valid Percent Cumulative
Percent
Valid
FT 34770 89.9 89.9 89.9
PT 3911 10.1 10.1 100.0
Total 38681 100.0 100.0
Table 11
From the table above, it can be observed that 89.9% of the students pursued full time studies
while 10.1% pursued part time studies.
Fee status descriptive
FEE_STATUS
Frequency Percent Valid Percent Cumulative
Percent
Valid
Domestic 32238 83.3 83.3 83.3
International 6443 16.7 16.7 100.0
Total 38681 100.0 100.0
Table 12

Data analysis 7
It can be observed that 83.3% (32,238) of the students are domestic students while 16.7% (6,443)
are international students.
Question three
a. Test for the difference in mean for aggression, thrill seeking and risk acceptance
scores by gender
Independent Samples Test
Levene's
Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed
)
Mean
Differe
nce
Std.
Error
Differe
nce
95% Confidence
Interval of the
Difference
Lower Upper
driver_agg Equal
variances
assumed
.11
7
.732 .083 38679 .934 .004 .050 -.093 .102
Equal
variances not
assumed
.083 18712.
803
.934 .004 .050 -.093 .102
thrill Equal
variances
assumed
.84
7
.357 -.37
0
38679 .711 -.005 .014 -.033 .022
Equal
variances not
assumed
-.37
1
18783.
250
.710 -.005 .014 -.033 .022
risk_accep Equal
variances
assumed
.05
4
.817 1.57
1
38679 .116 .078 .050 -.019 .176
Equal
variances not
assumed
1.57
1
18663.
180
.116 .078 .050 -.019 .176
Table 13

Data analysis 8
From the t-test table results above, it can be observed that the p-values computed are large
compared to the level of significance (0.05). This means that the mean aggression, thrill seeking
and risk acceptance scores do not differ by gender.
b. Test for the difference in mean for aggression, thrill seeking and risk acceptance
scores by metropolitan background status
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed
)
Mean
Differen
ce
Std.
Error
Differe
nce
95% Confidence
Interval of the
Difference
Lower Upper
driver_agg Equal
variances
assumed
1.060 .303 .71
4
32236 .475 .048 .067 -.083 .178
Equal
variances not
assumed
.71
9
7029.0
87
.472 .048 .066 -.082 .177
thrill Equal
variances
assumed
1.845 .174 .68
6
32236 .493 .013 .019 -.024 .050
Equal
variances not
assumed
.69
2
7048.1
78
.489 .013 .019 -.024 .049
risk_accep Equal
variances
assumed
3.228 .072 -.86
6
32236 .386 -.058 .067 -.189 .073
Equal
variances not
assumed
-.87
4
7040.4
76
.382 -.058 .066 -.188 .072
Table 14

Data analysis 9
From the t-test table results above, it can be observed that the p-values computed are large (0.3,
0.17 and 0.07) compared to the level of significance (0.05). This means that the mean aggression,
thrill seeking and risk acceptance scores do not differ by metropolitan background status.
c. Test for the difference in mean for aggression, thrill seeking and risk acceptance
scores by study mode.
Independent Samples Test
Levene's Test
for Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig.
(2-
tailed)
Mean
Differe
nce
Std.
Error
Differen
ce
95% Confidence
Interval of the
Difference
Lower Upper
driver_agg Equal
variances
assumed
.323 .570 -.30
9
3867
9
.757 -.023 .073 -.166 .121
Equal
variances
not
assumed
-.31
0
4834.
453
.757 -.023 .073 -.166 .121
thrill Equal
variances
assumed
.222 .637 .13
2
3867
9
.895 .003 .021 -.038 .043
Equal
variances
not
assumed
.13
2
4829.
635
.895 .003 .021 -.038 .043
risk_accep Equal
variances
assumed
.045 .832 -
2.2
69
3867
9
.023 -.167 .073 -.311 -.023
Equal
variances
not
assumed
-
2.2
61
4823.
706
.024 -.167 .074 -.311 -.022
Table 15

Data analysis 10
From the t-test table results above, it can be observed that the p-values computed are large (0.57,
0.63 and 0.83) compared to the level of significance (0.05). This means that the mean aggression,
thrill seeking and risk acceptance scores do not differ by study mode.
d. Test for the difference in mean for aggression, thrill seeking and risk acceptance
scores by RTA (follow up survey)
Independent Samples Test
Levene's
Test for
Equality of
Variances
t-test for Equality of Means
F Sig
.
t df Sig.
(2-
tailed
)
Mean
Differ
ence
Std.
Error
Differ
ence
95% Confidence
Interval of the
Difference
Lowe
r
Upper
driver_agg Equal variances
assumed
3179.
609
.00
0
-
93.
863
38679 .000 -
5.552
.059 -
5.668
-
5.436
Equal variances
not assumed
-
144
.45
4
11183.4
66
.000 -
5.552
.038 -
5.627
-
5.476
thrill Equal variances
assumed
1715.
363
.00
0
-
92.
063
38679 .000 -
1.539
.017 -
1.572
-
1.507
Equal variances
not assumed
-
133
.49
3
10036.6
97
.000 -
1.539
.012 -
1.562
-
1.517
risk_accep Equal variances
assumed
1951.
956
.00
0
-
78.
154
38679 .000 -
4.775
.061 -
4.895
-
4.655
Equal variances
not assumed
-
106
.20
9
9076.18
1
.000 -
4.775
.045 -
4.863
-
4.687

Data analysis 11
Table 16
From the t-test table results above, it can be observed that the p-values computed are less (0.00)
compared to the level of significance (0.05). This means that the mean aggression, thrill seeking
and risk acceptance scores differ significantly by RTA.
Question four
a. Depression by gender
Table of results
ANOVA
depression
Sum of Squares df Mean Square F Sig.
Between Groups .026 1 .026 .280 .597
Within Groups 3555.361 38679 .092
Total 3555.387 38680
Table 17
The anova results show that the computed p-value (0.57) is greater compared to the level of
significance (0.05). This means that the null hypothesis is accepted. It is concluded therefore that
null hypothesis is significant at 95% level of confidence.
b. Depression by metropolitan background status
Results table
ANOVA
depression
Sum of Squares df Mean Square F Sig.
Between Groups .010 1 .010 .114 .736
Within Groups 2962.189 32236 .092
Total 2962.200 32237
Table 18

Data analysis 12
The anova results show that the computed p-value (0.736) is greater compared to the level of
significance (0.05). This means that the null hypothesis is accepted. It is concluded therefore that
null hypothesis is significant at 95% level of confidence.
c. Depression by study mode
Results table
ANOVA
depression
Sum of Squares df Mean Square F Sig.
Between Groups .282 1 .282 3.072 .080
Within Groups 3555.105 38679 .092
Total 3555.387 38680
Table 19
The anova results show that the computed p-value (0.08) is greater compared to the level of
significance (0.05). This means that the null hypothesis is accepted. It is concluded therefore that
null hypothesis is significant at 95% level of confidence.
d. Depression by fee status
Results table
ANOVA
depression
Sum of Squares df Mean Square F Sig.
Between Groups .000 1 .000 .003 .956
Within Groups 3555.387 38679 .092
Total 3555.387 38680
Table 20
The anova results show that the computed p-value (0.956) is greater compared to the level of
significance (0.05). This means that the null hypothesis is accepted. It is concluded therefore that
null hypothesis is significant at 95% level of confidence.

Data analysis 13
Question five
- Binary logistic regression (RTA and Demographics).
Table of results
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
Age_category -.003 .000 42.072 1 .000 .997
GENDER -.262 .033 64.299 1 .000 .769
LIVING_ARRANGE -.049 .019 6.801 1 .009 .952
FEE_STATUS .248 .041 36.290 1 .000 1.282
Constant -1.673 .031 2885.476 1 .000 .188
a. Variable(s) entered on step 1: Age_category, GENDER, LIVING_ARRANGE, FEE_STATUS.
Table 21
From the results table above, it can be observed that the value of the coefficient for the living
arrangement is -0.049. This value is close to zero. It is an indication that there is no association
between RTA and living arrangement. To add on, the odds of the predictor variables are tending
towards 1, this is an indication that they cause a great variation in RTA if they are increased.
- Binary logistic regression (RTA and driving distance).
Results table
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
dist_driving -.016 .031 .268 1 .605 .984
Constant -1.885 .024 5937.971 1 .000 .152
a. Variable(s) entered on step 1: dist_driving.
Table 22
From the results table above, it can be observed that the value of the coefficient for the driving
distance is -0.016. This value is close to zero. It is an indication that there is no association
between RTA and driving distance. The odd of the predictor variable is 0.94 indicating a strong
influence on RTA.

Data analysis 14
- Binary logistic regression (RTA with aggression, thrill seeking and risk acceptance).
Table of results
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
Driver
aggression
.612 .024 661.998 1 .000 1.844
thrill .516 .078 43.584 1 .000 1.675
Risk
acceptance
.596 .009 4017.531 1 .000 1.815
Constant -17.579 .327 2887.675 1 .000 .000
a. Variable(s) entered on step 1: driver_agg, thrill, risk_accep.
Table 23
From the results table above, it can be observed that the values of the coefficients for the
predictor variables are 0.61, 0.52 and 0.596. It is an indication that there are significant
associations between RTA and predictor variables. To add on, the odds of the predictor variables
are tending towards 1, this is an indication that they cause a great variation in RTA if they are
increased.
Question six
- Binary logistic regression (OB and Demographics).
Results table
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
Age_category -.003 .000 40.576 1 .000 .997
GENDER -.267 .033 66.548 1 .000 .766
LIVING_ARRANGE -.012 .017 .447 1 .504 .988
Constant -1.654 .031 2863.657 1 .000 .191
a. Variable(s) entered on step 1: Age_category, GENDER, LIVING_ARRANGE.
Table 24

Data analysis 15
From the results table above, it can be observed that the value of the coefficient for the living
arrangement is -0.012. This value is close to zero. It is an indication that there is no association
between obesity at third year follow up and living arrangement.
- Binary logistic regression (OB and overweight and depression).
Table of results
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
depression 1.787 .037 2325.596 1 .000 5.970
BL_owob -.017 .032 .270 1 .603 .983
Constant -2.186 .027 6644.566 1 .000 .112
a. Variable(s) entered on step 1: depression, BL_owob.
Table 25
- Binary logistic regression (OB and edu_par and presence or absence of obese).
Table of results
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1a
owob_par 1.881 .169 124.423 1 .000 6.561
edu_par -2.210 .061 1331.774 1 .000 .110
Constant -2.826 .170 277.272 1 .000 .059
a. Variable(s) entered on step 1: owob_par, edu_par.
Table 26
The odds of the predictor variable (parents university education) is low (0.11), this is an
indication that it causes minimal variation in obesity if they are increased.