T-TEST AND ANOVA

QUESTION

PSY392
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English Competency
5% of the total marks have been allocated to spelling,
grammar, punctuatiory and overall
language
use.
Relevant Course Materials
This TMA covers
the
course materials in
Study Unit 3.
You
should read the relevant sections in
the textbook and the Study Guide before you attempt your TMA. In addition,
you should
refer
to Seminar slides
and discussion notes
used
in
class.
You
may
find
it necessary to read
up on
other materials beyond
the textbook
and
the
Study Guide in order to add depth to
your
answers.
SIM. UNIVERSITY
::,
Knouledge
and skills being
assessed
in this TMA:
The
question is designed
to assess
your knowledge
and
ability to:
(i)
use SPSS to generate
inferential
statistics for
hypothesis testing.
(ii)
interpret the results
generated
from the
SPSS output.
Hou to
approach this Assignment
(a)
For this assignment,
you have
to make use
of the data
set provided to run
SPSS
commands. This dataset
contains the
survey data
of
adult learners
pursuing
part-time
degree
programmes in a
private university in Singapore.
[SPSS
Filename : TMA02_Adult_Learning.
sav]
(b) Read
the
requirements
of
each question and
generate the appropriate
SPSS output for
your analysis and
interpretation.
Referencing in APA format
Marks allocation at a glance
Q1
Q3

(39
marks)
(a)
13
Q2
(b)
(c)
(21marks) (a)
2
5 marks
will
be deducted
for
missing references
or inaccurate formatting
Marks
Word
limit
(b)
5
(c)
5
(d)
(e)
5
4
73
13
15
Q4
20 550-600
English competency
5
Total
100
1000
(excluding
Q4)
PSY392,.:
Question
(a)
(b)
1
(39
,fl
marks)
:=:
:..
:.
Perform
inferential
statistical
analysis to
test if there
are significant
differences in
the
quality
of
life
between male
and female
adult learners
before pursuing
adult
education.
Test your hypotheses
at
the 5%
significance level.
Present
the
SPSS output
that you have
generated
and answer
the following
questions:
(i)
Identify
an appropriate
test
statistic that
you should
use for the
analysis. (2
marks)
(ii)
Explain why
you chose
to use this test
statistic.
(2
marks)
(iii)
Give a step-by-step
intelpretation
of
the
SPSS
output by:
r
Stating
the null and
alternative hypotheses,
(2
marks)
e
Reporting
in APA format
the statistical test
result for
the analysis. (7
marks)
Perform inferential
statistical analysis
to test
if
there are
significant differences
in the
quality
of
life
of the adult learners
before
they pursued
adult education
and
one year
after
their graduation.
Test your
hypotheses at
the 5% significance level.
Present
the SPSS
output that you have
generated
and answer
the following questions:
(i)
Identify an
appropriate
test statistic that
you should use for
the analysis. (2
marks)
(ii)
Explain why
you chose to
use this test statistic
(2
marks)
(iii)
Give
a
step-by-step interpretation
of the SPSS
output by:
o
Stating the null and
altemative hypotheses,
(2
marks)
o
Reporting
in APA format
the statistical
test result for
the analysis. (7
marks)
sffi,ii8–JVlF,slr*’:=.
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TMAOA
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PSY392
TMAO?
(c)
Perform inferential
statistical analysis
to test if there
are significant
differences in the
quality of life
of adult learners
of
various
age groups
one year
after their graduation.
Teit your
hypotheses at
the 5% significance level.
Present the
SPSS output
that
you
have
generated.
Post hoc test is
not required. Answer
the following
questions:
(i)
Identify
an appropriate
test statistic that you
should use for the
analysis.
(2
marks)
(ii)
Explain why
you chose to use this test
statistic. (2
marks)
(iii)
Give a step-by-step interpretation
of the SPSS output by:
Question
o
Stating the null and altemative
hypotheses, (2
marks)
o
Reporting in APA format
the statistical test result for
the
analysis.
[Note:
2:
(15
You
should
also report descriptive
statistics in an APA formatted table.]
marks)
Using
2-way
contingency
tables, test for the association
between
reasons for pursuing
adult
education and
age.
(Hint:
Consider
whether you
should use the actual or recoded variable
for’age’.) Test your hypothesis at the
5% significance
level. Remember
to show
your
SPSS
output
for your
statistical test.
(a) (i)
Identify an appropriate test statistic that you should use for the above analysis.
(ii)
Explain why you chose to use this test statistic.
(b)
Give
a step-by-step interpretation
of
the
SPSS output
by:
(,
Stating the
null
and altemative hypotheses,
(i0
Stating
the
effect size,
(iii) Interpreting
the effect size,
(iv)
Reporting in APA format the statistical test result for the analysis.
SIM UNIVERSIITY
I
”,.:rl
(7
marks)
(2 marks)
(2
marks)
(2
marks)
(1mark)
(1mark)
(7
marks)
‘TMA02-5
PSY392
Question
3
l.
r,
(21marks)
(b)
(i)
State
the value
of
‘r’
in the
above
analysis.
(ii)
Explain
what’r’
is
and what’r’
in your
analysis
means.
(c)
(i)
State the value
of
‘r2′ in
the above
analysis,
(ii)
Explain
what’ll
is and what
12in
your analysis
means.
.r.l’
.’::
..,1
Perform
a
regression
analysis
to assess
and
explain the
relationship
between
age
of the adult
learners
(Hint:
Consider
whether
you
should
use the
actual
or recoded
variable
for’age,,)
who participated
in
the
survey
and their levels
of depression
(as
Depression
Inventory,
the higher
the
score, the higher
the
level
of depression).
Remember
to show the
SPSS
output that
you have
generated
for
the
above analysis.
(a)
Identify
the dependent
and independent
variables
in
the regression
analysis.
(d)
Based
on the regressiontnodel
generated,
(e)
(i)
Derive
the regression
equatiory
(i0
Explain
the usefulness
of the regression
equation.
\A/hat
depression score
would
an adult leamer
likely
to get if he is
34
years
old?
[Note:
Question
4:
Show
your
calculations clearly.]
(20
marks)
t=:jfMAg?.
measured
by the Beck
Based
on
the
SPSS
outputs
generated
in
each
of
the
above
statistical analysis
that
you have
performed
in
Questions
L
to 3, briefly
discuss the
survey results, relating
your
analysis
and
discussion to the
context
of Singapore
society.
Your
analysis
should be
written in approximately
550-600
words. You
may wish to
include relevant
literature to
substantiate
your
discussion.
[Note:
srrrl utilrve[s1]y.:
?
i..€.’
‘,li
i”
]
i,,,i
,€
‘,,.i
:
(2
marks)
(2
marks)
(3
marks)
(2
marks)
(3
marks)
(3
marks)
(2
marks)
(4
marks)
:::. .:,,.,11
:.:y$696217;
English Competency
(5
marks)
English competenry
is an assessable
component of
all TMAs and 5″/o of
the total marks
for each
TMA have been allocated
to this component.
This component
refers to your
spelling,
punctuation, gr;[nmar and overall
language
use.
Referencing
Please do note
that you
have to use proper
referencing
in your
TMA writing, especially
when
you
include
materials or
information gathered
from
any
published
sources. You should
refer to
the
“Guidance on Referencing
in APA
format”, which
is available
in Blackboard,
to have
a
better
idea how to
do your referencing.
FIVE
(5)
marks
will be
deducted unless
these
are
presented accurately
in APA format.

End of TMA02

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TMA02: lnfer enti al St ati sti cs
This
tutor-marked assignment
(TMA)
is worth
25%
of
the final mark for PSY392 Methods of
Data Analysis: Exploring Behavioural Sciences.
This
assignment
requires
you
to
perform
quantitative statistical
data analysig using inferential statistics generated
by the
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(Student
version).
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Apr;
I
zot
z
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sIM:UNIVERSTY*
should
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TMAO2-2

SOLUTION

Ans 1

i>

Here we use Independent sample T-test statistic.

ii>

We want to test there are significant differences in the quality of life between male and female adult learners before pursuing adult education. So we use independent sample T-test.

 

iii>

 

NULL HYPOTHESIS : there are no significant differences in the quality of life between male and female adult learners before pursuing adult education.

ALTERNATIVE HYPOTHESIS : there are significant differences in the quality of life between male and female adult learners before pursuing adult education.

 

 

 

 

 

T-Test

Group Statistics

) female, 1 male

N

Mean

Std. Deviation

Std. Error Mean

Quality of Life Before pursuing Adult Education Female

157

59.52

10.176

.812

Male

119

59.73

8.036

.737

 

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

Quality of Life Before pursuing Adult Education Equal variances assumed

8.290

.004

-.192

274

.848

-.218

1.132

-2.446

2.011

Equal variances not assumed

-.199

273.522

.843

-.218

1.096

-2.376

1.941

 

From t-test for equality of means we see that alternative hypothesis is rejected at 5% level of significance and null hypothesis is accepted. Then we conclude that there are no significant differences in the quality of life between male and female adult learners before pursuing adult education.

 

 

b.

i>

Here we use paired sample T-test statistic.

ii>

We want to test there are significant differences in the quality of life of the adult learners before they pursued adult education and one year after their graduation.

iii>

NULL HYPOTHESIS : there be no significant differences in the quality of life of the adult learners before they pursued adult education and one year after their graduation.

ALTERNATIVE HYPOTHESIS: There be a significant differences in the quality of life of the adult learners before they pursued adult education and one year after their graduation.

 

 

 

 

 

 

 

 

 

 

T-Test

Paired Samples Statistics

 

Mean

N

Std. Deviation

Std. Error Mean

 
Pair 1 Quality of Life Before pursuing Adult Education

59.61

276

9.298

.560

 
Quality of Life One Year After Graduation

63.56

276

9.307

.560

 

 

 

 

 

 

 

 

 

 

 

 

 

Paired Samples Correlations

 

N

Correlation

Sig.

 
Pair 1 Quality of Life Before pursuing Adult Education  & Quality of Life One Year After Graduation

276

.658

.000

 

Paired Samples Test

Paired Differences

t

df

Sig. (2-tailed)

Mean

Std. Deviation

Std. Error Mean

95% Confidence Interval of the Difference

Lower

Upper

Pair 1 Quality of Life Before pursuing Adult Education  – Quality of Life One Year After Graduation

-3.948

7.695

.463

-4.860

-3.036

-8.524

275

.000

 

From paired sample t-test we see that alternative hypothesis is accepted at 5% level of significance that means there are significant differences in the quality of life of the adult learners before they pursued adult education and one year after their graduation.

 

c.

i>

Here we use one way ANOVA test as statistic.

ii>

We want to test if there are significant differences in the quality of life of adult learners of various age groups one year after their graduation.  And these are generated from same population so we use one way ANOVA test.

 

iii>

NULL HYPOTHESIS : there are no significant differences in the quality of life of adult learners of various age groups one year after their graduation.

ALTERNATIVE HYPOTHESIS: there are significant differences in the quality of life of adult learners of various age groups one year after their graduation.

Oneway

Descriptives

Quality of Life One Year After Graduation

N

Mean

Std. Deviation

Std. Error

95% Confidence Interval for Mean

Minimum

Maximum

Lower Bound

Upper Bound

18 to 27

45

57.40

7.835

1.168

55.05

59.75

44

80

28 to 37

90

62.37

9.184

.968

60.44

64.29

43

80

38 to 47

64

64.45

9.134

1.142

62.17

66.73

49

91

48 to 57

60

67.45

8.146

1.052

65.35

69.55

53

86

58 to 67

17

69.06

8.422

2.043

64.73

73.39

56

82

Total

276

63.56

9.307

.560

62.46

64.66

43

91

 

 

 

 

 

 

 

 

 

 

ANOVA

 
Quality of Life One Year After Graduation  

Sum of Squares

df

Mean Square

F

Sig.

 
Between Groups

3308.722

4

827.180

10.928

.000

 
Within Groups

20513.351

271

75.695

 
Total

23822.072

275

 
 

 

 

 

 

 

 

 

 

 

Post HocTests

Multiple Comparisons

Quality of Life One Year After Graduation
LSD
(I) 5 groups from 18 to 67 (J) 5 groups from 18 to 67

Mean Difference (I-J)

Std. Error

Sig.

95% Confidence Interval

Lower Bound

Upper Bound

18 to 27 28 to 37

-4.967

1.588

.002

-8.09

-1.84

38 to 47

-7.053

1.693

.000

-10.39

-3.72

48 to 57

-10.050

1.716

.000

-13.43

-6.67

58 to 67

-11.659

2.477

.000

-16.54

-6.78

28 to 37 18 to 27

4.967

1.588

.002

1.84

8.09

38 to 47

-2.086

1.423

.144

-4.89

.71

48 to 57

-5.083

1.450

.001

-7.94

-2.23

58 to 67

-6.692

2.301

.004

-11.22

-2.16

38 to 47 18 to 27

7.053

1.693

.000

3.72

10.39

28 to 37

2.086

1.423

.144

-.71

4.89

48 to 57

-2.997

1.563

.056

-6.07

.08

58 to 67

-4.606

2.374

.053

-9.28

.07

48 to 57 18 to 27

10.050

1.716

.000

6.67

13.43

28 to 37

5.083

1.450

.001

2.23

7.94

38 to 47

2.997

1.563

.056

-.08

6.07

58 to 67

-1.609

2.390

.502

-6.32

3.10

58 to 67 18 to 27

11.659

2.477

.000

6.78

16.54

28 to 37

6.692

2.301

.004

2.16

11.22

38 to 47

4.606

2.374

.053

-.07

9.28

48 to 57

1.609

2.390

.502

-3.10

6.32

 

 

From this ANOVA table we see that alternative hypothesis is accepted at 5% level of significance and reject the null hypothesis means there are significant differences in the quality of life of adult learners of various age groups one year after their graduation.

 

And from the multiple comparison post hoc test shows that the groups between (48 to 57) and (58 to 67) and groups (28 to 37) and (38 to 47) has no significant differences at 5% level of significance otherwise between other groups almost a significant difference occurred at 5% level of significance.

2.

a.

i>

Chi-square test statistics is appropriate for the about analysis.

ii>

To test for the association between reasons for pursuing adult education and age chi-square test statistic is the best.

 

 

b.

i>

Null hypothesis: there be no difference between observed and expected frequencies

Alternative hypothesis: there be a difference between observed and expected frequencies

 

ii> I don’t know about effect size.

iii> I don’t know about this.

iv>

 

Crosstabs

 

 

 

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

5 groups from 18 to 67 * Reason for Adult Education

276

100.0%

0

.0%

276

100.0%

 

 

5 groups from 18 to 67 * Reason for Adult Education Cross tabulation

Count

Reason for Adult Education

Total

career advancement

career change

social/personal

self satisfaction

5 groups from 18 to 67 18 to 27

29

6

6

4

45

28 to 37

22

48

13

7

90

38 to 47

8

46

5

5

64

48 to 57

31

14

8

7

60

58 to 67

0

2

2

13

17

Total

90

116

34

36

276

 

 

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

127.650a

12

.000

Likelihood Ratio

107.515

12

.000

Linear-by-Linear Association

16.440

1

.000

N of Valid Cases

276

a. 2 cells (10.0%) have expected count less than 5. The minimum expected count is 2.09.

 

 

 

Symmetric Measures

Value

Approx. Sig.

Nominal by Nominal Contingency Coefficient

.562

.000

N of Valid Cases

276

 

From the chi-square test table we see that alternative hypothesis is accepted at 5% level of significance that means there be a difference between observed and expected frequencies.

 

 

 

 

 

3.

 

  1. a.    Here the dependent variable is BDI and the independent variable is Age.

 

 

 

 

 

Regression

Descriptive Statistics

Mean

Std. Deviation

N

Beck Depression Inventory Before pursuing Adult Education

23.05

15.033

276

Age

39.17

11.095

276

Correlations

Beck Depression Inventory Before pursuing Adult Education

Age

Pearson Correlation Beck Depression Inventory Before pursuing Adult Education

1.000

.137

Age

.137

1.000

Sig. (1-tailed) Beck Depression Inventory Before pursuing Adult Education

.

.012

Age

.012

.

N Beck Depression Inventory Before pursuing Adult Education

276

276

Age

276

276

Variables Entered/Removedb

Model

Variables Entered

Variables Removed

Method

1 Agea

.

Enter

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1 Regression

1162.232

1

1162.232

5.222

.023

Residual

60987.953

274

222.584

Total

62150.185

275

 

 

 

 

 

 

 

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1 (Constant)

15.797

3.300

4.786

.000

Age

.185

.081

.137

2.285

.023

 

 

 

 

 

 

 

Coefficient Correlationsa

Model

Age

1 Correlations Age

1.000

Covariances Age

.007

b.

i>

Here the value of r is 0.137

ii>

That indicates the linear relationship between two variables be 0.137

c.

i>

the value of r^2 is 0.137^2=0.0188

ii>

it indicates only (+)ve values of the linear relationship between two variables.

d.

i>

The regression equation is-

BDI= 15.797 + 0.185*age

ii>

from this regression equation we predict the value of BDI at various age.

e.

i>

The value of BDI at the age of 34 be-

15.797 + 0.185*34=22.087

JH73

“The presented piece of writing is a good example how the academic paper should be written. However, the text can’t be used as a part of your own and submitted to your professor – it will be considered as plagiarism.

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