Interpreting Statistical Findings

This study examines the relationship between test time and BDI scores in a group of individuals not receiving treatment. Descriptive statistics and tests of within-subjects effects are used to analyze the data. The results support the hypothesis of improvement in BDI scores over time with no intervention. Pairwise comparisons show no significant differences in BDI scores between test times. Regression analysis is also conducted to explore the relationship between optimism, physical exercise, and BDI scores.

Section C: Interpreting Statistical findings
A study tracked depression scores over time in a group of 53 self-selecting individuals who were
not receiving any treatment. Depression was measured using the Beck Depression Inventory (BDI,
Beck, 1961) where higher scores represented greater reported depression.
BDI scores were taken at the study outset (baseline), at 3 months and again at 12 months. The
research team tested the first hypothesis that there would be an improvement in BDI scores over
time with no intervention.
Descriptive
Statistics
Mean Std. Deviation N
Baseline BDI Depression
Scores 13.3396 2.57162 53
Post-Test (3 Months) BDI
Depression Scores 10.9245 2.54837 53
Post-Test (12 months) BDI
Depression Scores 8.8113 2.47337 53
Mauchly's Test of Sphericitya
Within Subjects Effect Mauchly's W
Approx. Chi-
Square df Sig.
TestTime .522 33.188 2 .000
Tests of
Within-
Subjects
Effects
Measure:
MEASURE_1
Source
Type III Sum of
Squares df Mean Square F
S
i
g
.
TestTime Sphericity Assumed
544.201 2 272.101 226.149
.
0
0
0
Greenhouse-Geisser
544.201 1.353 402.258 226.149
.
0
0
0
Huynh-Feldt 544.201 1.376 395.430 226.149 .

0
0
0
Lower-bound
544.201 1.000 544.201 226.149
.
0
0
0
Error(TestTime) Sphericity Assumed 125.132 104 1.203
Greenhouse-Geisser 125.132 70.349 1.779
Huynh-Feldt 125.132 71.564 1.749
Lower-bound 125.132 52.000 2.406
Pairwise Comparisons
Measure: MEASURE_1
(I) TestTime (J) TestTime
Mean Difference
(I-J) Std. Error Sig.b
95% Confidence Interval for
Differenceb
Lower Bound Upper Bound
1 2 2.415* .191 .000 1.942 2.888
3 4.528* .276 .000 3.847 5.210
2 1 -2.415* .191 .000 -2.888 -1.942
3 2.113* .154 .000 1.732 2.494
3 1 -4.528* .276 .000 -5.210 -3.847
2 -2.113* .154 .000 -2.494 -1.732
Based on estimated marginal means
*. The mean difference is significant at the .05 level.
b. Adjustment for multiple comparisons: Bonferroni.
Questions 12-16 are based on the study SPSS output directly above and on the previous page
(4 marks each unless stated).
12) Name in full the statistical test used that has produced the SPSS output here (2 marks).
Mauchly's Test of Sphericity is used in order to determine the relationship between two factors

13) Name the ‘independent variable’ (or factor) and each of the ‘levels’. Please also identify and
precisely name the dependent variable.
Independent variable: Test time
Dependent variable: BDI
14) Can Sphericity be assumed in this study? Please explain your interpretation.
Yes, Sphericity can be assumed in this study by comparing each pair of treatment level that
assist to determine the score in BDI.
15) Was the first hypothesis supported? (Please explain/interpret the findings in full sentences
using statistical notation i.e. f-ratio, dfx2 and significance/p-value).
Yes, the first hypothesis is supported because the value of p is lower than 0.05 (standard
criteria) as a a result, there is a significant relationship between improvement in BDI scores
over time with no intervention. Therefore, alternative hypothesis is accepted over other. Also,
the outcomes reflected that the level of depression scores will be decreases over time without
any intervention.
16) In testing pairwise comparisons (Bonferroni post-hoc test), which BDI mean score comparisons
were significantly different from each other over time? Please also refer to the direction of any
significant differences.
There is no significant difference between the BDI scores and test time because all the p-
values are lower than 0.05 and that is why, direction reflected that if the test time increases, the

score of BDI will also increases.

As part of the same study, optimism ratings (from the life orientation test revised, LOT-R, Carver et
al., 2010; higher scores = more reported optimism) and amount of physical exercise (in hours, per
week) were also captured when the study commenced.
Researchers then tested the second hypothesis that levels of optimism (from the LOT-R) and
amount of physical exercise would predict BDI baseline scores using a different statistical test.
Model
Summary
Mode
l R R Square
Adjusted R
Square
Std. Error of the
Estimate
1 .732a .536 .517 1.78701
a. Predictors:
(Constant),
Physical
exercise (in
hours) per
week,
Optimism
score
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 184.217 2 92.108 28.843 .000b
Residual 159.670 50 3.193
Total 343.887 52
a. Dependent
Variable:
Baseline BDI
Depression
Scores
b. Predictors:
(Constant),
Physical
exercise (in
hours) per
week,
Optimism
score
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.

B Std. Error Beta
1 (Constant) 18.205 .686 26.535 .000
Optimism score -.391 .078 -.574 -5.028 .000
Physical exercise (in hours)
per week -.635 .302 -.240 -2.103 .041
a. Dependent
Variable:
Baseline BDI
Depression
Scores
Questions 17-22 are based on the SPSS output directly above (4 marks each unless stated):
17) From examining the SPSS output for the second hypothesis, please name in full the statistical
test that was conducted (2 marks).
Regression analysis is performed that assist to examine the relationship between two factors.
18) Please write the formula for a regression line below (for a single predictor variable).
Y = a+ bx
Then define each component of the formula with reference to the research above (you may choose
to cite relevant values from the coefficients table)
By referring the formula,
y = dependent variable
X = independent variable
b is the slop of a line and
So Y = -0.635 x+18.205

19) Please then interpret if the research team’s second hypothesis was supported (2 marks each).
a) How much variance in BDI scores was predicted?
53%
b) Does the regression model significantly predict outcome? (include any relevant statistics here to
support your interpretation – please write in a sentence)
The regression model shows that there is significant difference between mean value of BDI
and physical exercise per week because as per the standard criteria, the value of P is lower
than 0.05 and that is why, alternative hypothesis is accepted.
20) Which was the strongest individual predictor of variance in BDI scores and how can the
relationship be explained? (examine the output closely to determine this and please answer in a full
sentence, citing relevant statistics, e.g. Beta coefficient, p-value)
Optimum score is the strongest predictor of variance in BDI scores because statistics shows
that there is a significant difference between the mean value of both variable i.e. 0.00<0.05.
Thus both variable move in same directly and if the value of test time increases, BDI score
also increases.
21) Did the second predictor variable significantly predict variance in BDI scores (please answer in
a full sentence, citing relevant statistics)
Yes, there is a significant difference between the second predictor and BDI because the value
of P (0.04) is lower than 0.05 and that is why, physical exercise in per week predict the

variance in BDI scores.
22) Please answer either part (a) or (b) (both 4 marks).
a) If physical exercise was theorised to mediate (i.e. explain) the relationship/pathway between
optimism and BDI scores, please outline briefly one way in which this could be tested statistically
(4 marks).
The one way in which the relationship between optimism and BDI can be tested is the use of
correlation. This is particularly because of the reason that correlation will help in identifying
the relation among the optimism and the BDI score. If there will be any relation, then this will
be outlined by using correlation as this test the direct link between the two variables.
Or:
b) Please consider some implications of the second part of the study. Could you suggest anything
that might have a positive impact on BDI scores in those reporting being affected by depression?
And/or outline briefly some future research possibilities? (4 marks)

Section D: Designing a study (30 marks)
A health psychologist has received funding to design a study to see how exercise could be promoted
in adults working in offices. Your task is to design a study to explore this and fill in the APA report
sections starting below. You may find it helps to plan the study on a separate piece of paper before
beginning to answer.
Think about how you could promote exercise. This may involve testing a particular intervention
which may potentially increase or initiate exercise. Think how you could test and measure whether
any intervention has had any effect.
Alternatively, you could consider some psychological and demographic (e.g., age) factors you think
will influence exercise. Study findings may then indicate where an intervention to promote
exercise could be targeted. Do also consider very briefly how such an intervention might be
implemented as you consider your results.
Perhaps a qualitative approach would be just as beneficial? This could involve office workers who
already exercise. What could you learn from such individuals?
You may wish to use references in places (e.g., for questionnaires) for this section.
Do be guided by the marks available per question in terms of how much you should write for each
section (e.g., one mark could be gained by one relevant sentence).
Brief aims and research question (hypotheses optional) (6 marks):
The aim of the study is to investigate the ways through which exercise could be promoted
among adults who are working in office: A study on Red Bull UK
Objectives:
 To understand the concept of exercise promotion.
 To identify the factors which will motivate the habit of exercising among adults
 To assess the various methods for promotion of exercise among working adults.
 To recommend the best ways through which exercise can be promoted among working
adults.
Method (3 marks for each subsection)
Study Design (if quantitative please explain/describe and name variables e.g., IV/DV,
predictors/outcome):

Research type: In order to determine the method of promoting exercise, qualitative study has
been adopted because it provide in-depth analysis of the relevant factors.
Participants & Sampling details:
Sampling: The study is based upon qualitative study and that is why, scholar uses simple
random sampling method in which 20 employees of Red Bull UK has been selected. With the
help of chosen sampling method, scholar analyze the ways to promote exercise among adults
who are working in offices.
Materials/measures (if qualitative, e.g., some example interview/focus group questions. For
quantitative studies, do consider how all variables in your proposed study will be measured,
including ‘exercise’.):
For the purpose of conducting the research, material or measure used will be the interview
questions. The interview questions are as follows-
1. Are you aware of the importance of using exercise among working adults?
2. According to you are there any factors which influences the exercising pattern among
the adults working?
3. Are there any benefits of using exercising by working adults?
4. What are some of the methods of through which exercising can be promoted among the
adults?
5. What are some of the challenges which might be faced by working adults in
exercising?
6. Are there any suggestion through which you can motivate adults to use different
methods of exercising among the adults?

Procedure:
The procedure for the completion of the study over the ways through which exercise could be
promoted among adults who are working in office is to take interview from the different
adults. This interview method will assist in getting the views of different people over the
exercising by the adults. For this 20 employees of company will be selected and then these
questions will be asked to them and as per their outcome the result is being analyzed.
Intended analysis and forecast results (6 marks):
The present study intends to provide result relating to the study over people that is working
adults are using exercising or not. The intended outcome of the study is that there is
requirement of people to adapt to exercising as this will decrease their stress and will assist
them in improving their working efficiency. The use of exercising will enlighten the mood of
person while working and will increase enthusiasm in them.
Forecast Discussion (e.g. strengths & limitations, study implications) (6 marks)

The strength of this study is that this will involve the personal interaction with the respondent.
This will assist researcher in dealing with the respondent personally and they can interact with
the respondent and understand their behavior as well.
The limitation of this study is that this involves the involvement of only 20 respondents and it
might be possible that this does not provide a clear picture of the research.
The implication of the study is that in future the researcher must make use of the quantitative
study as this will assist the researcher in providing a better view of the company. The other
implication of the study is that this must increase the number of sample. This is particularly
because of the reason that more sample will provide more clear view of data.