1.1 A researcher ran an experiment where a large sample of volunteers placed their hand into a bucket of ice water on two occasions – once before being given the drug Hurtbegone, and once after being given the drug.

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Critical Analysis

This assessment consists of two distinct parts and constitutes 25% of your overall grade for this course. Your responses will be graded in line with the grading criteria described in “Grading Criteria (Critical Analysis).pdf” on the PSYC1065 module page.

1 Part A. Research Critiques (60 marks)

Word limit: There is no minimum word limit, but your responses to each of the 6 individual scenarios should not exceed an absolute maximum of 200 words (many questions can be answered in 100 - 150 words).

The conclusions made in each of the hypothetical research scenarios are undermined by at least one fundamental weakness in some aspect of either the research design (Scenarios 1.1 - 1.4) or the interpretation of the data (Scenarios 1.5- 1.6). For each scenario, you must (a) identify one weakness and describe how this might threaten the validity of the conclusions made, and (b) suggest how the design (1.1 - 1.4) or handling of the data (1.5 - 1.6) might be revised to provide a better assessment of the claims made (if you don’t believe remedial solutions are possible you should state why).

It is not a requirement to include references in your answer (although you may do so if relevant) but further reading is recommended in order to enhance your ability to recognise common research design issues. A graded example for Part A is provided  in “Example Answer Part A (Critical Analysis).pdf” on Moodle. You may also find the Meltzoff and Cooper (2018) text (see module handbook for details) a useful guide for tackling this part of the assignment.

Scenarios 1.1 - 1.4: Research Design

1.1 A researcher ran an experiment where a large sample of volunteers placed their hand into a bucket of ice water on two occasions – once before being given the drug Hurtbegone, and once after being given the drug. Pain ratings were significantly lower after being given the drug (p<.001) so the researcher concluded that Hurtbegone is an effective treatment for pain.

1.2 The graph below shows the relationship between maternal weight gain during pregnancy and the percentage of cases of pre-eclampsia, a potentially serious disorder of pregnancy characterised by high blood pressure (data shown is hypothetical). A team of medical researchers analysed these data and found a highly significant association (p<.001), and so concluded that weight gain should be restricted during pregnancy in order to minimise the likelihood of pre-eclampsia.

1.3 A lecturer was committed to helping the poorest performing students. To this end, he administered a 15-minute test to his class of 200 pupils. The poorest performing 20 were given a new multimedia style teaching method in seminars for the rest of the year. He also had a control group of the best performing 20 pupils (who received his usual teaching). At the end of the year he administered another 15-minute test and found that scores of poorest students had significantly improved, while the control groups scores had actually got significantly worse. He concluded that his new technique was more effective and he would implement this en masse the following year.

1.4 A team of researchers discovered that the average life expectancy of cello players was significantly higher than the population life expectancy as a whole. They concluded that playing the cello as a career is linked to a longer life than other careers.

Scenarios 1.5 - 1.6: Data interpretation

1.5 A group of researchers speculatively explored whether happiness might be affected by month of the year. After looking at the below graph of data collected from a random sample of 200 people who rated happiness each month for a year, the researchers believed that March resulted in the lowest mood and September the highest mood. A paired t-test found a significant difference between these two months (p=.047), and so the researchers concluded that people’s happiness is highest in September and lowest in March.

1.6 A teacher wondered whether classroom temperature had any impact on student learning. She measured scores of all students on a maths test at the start of term, consistently taught one class of students in a hot room and the other in a warm room, then gave another maths test at the end of the term. A paired t-test showed a significant improvement at the end of term compared to the start of term in math scores for those taught in the warm room (p=.039). While scores for those taught in a hot room were slightly elevated at the end of term, this was not significant (p=.097). She concluded that being taught in a warm room resulted in a significantly greater improvement in maths test scores compared to being taught in a hot room.

2 Part B. Mini-report (40 marks)

There is a maximum word limit of 800 words for the mini-report, with no minimum word limit. The SPSS output you need to tackle this question is in Appendix A at the end of this document.

A research team wanted to test the hypothesis that depressed mood would improve after a session of Reiki, but would not change after a session of counselling. They tested this by randomly allocating half of a sample of depressed participants to receive counselling and the other half to receive Reiki (SPSS variable intervention) and assessed depressed mood before (pre) and after (post) each treatment (SPSS variable time). Depression scores were measured such that higher scores indicated greater depression.

Write a Methods and Results section using the information contained in the SPSS output in Appendix A, as well as a very brief summary of findings in a Discussion section. You have not been provided with all of the information you would need to present every element of a Methods and Results section. However, you should try to complete all the aspects of these sections where the information provided to you allows you to do so. In some instances, you have been given limited information, but further investigative work (e.g. an internet search) will provide the more detailed information you need.

What you need to submit: Your report should be presented using APA guidelines, as required for your first assessment (the quantitative lab report). It should contain (A) a Methods section (all elements except the Procedure section, as you have been given minimal on procedural details), (B) a Results section, and (C) a Discussion section no longer than 50 words which provides a brief statement on whether the results supported the hypothesis. You should include references if these are relevant to your report (although there should be no need to include more than a handful of references)

Statistics

Gender

Ethnicity

Age

N

Valid

120

120

117

Missing

0

0

3

Gender

 

Frequency

 

Percent

Valid Percent

Valid

Female

54

45.0

45.0

Male

66

55.0

55.0

Total

120

100.0

100.0

 

Ethnicity

Frequency

 

Percent

Valid Percent

Valid

White

60

50.0

50.0

Asian

29

24.2

24.2

Black or African American

31

25.8

25.8

Total

120

100.0

100.0

Descriptives

N

Minimum

Maximum

Mean

Std. Deviation

Age

117

20.08

48.05

33.50

6.00

Valid N

117

 

 

 

 

Graph

General Linear Model

Within-Subjects Factors

 
 


Measure:MEASURE_1

 

 

Between-Subjects Factors

Value Label

N

Intervention

1.00

Reiki

60

2.00

Counselling

60

 

DescriptiveStatistics

 

 

 

Std.

 

 

 

Intervention

Mean

Deviation

N

 

BDI-II (pre)

Reiki

33.4540

3.97698

 

60

 

Counselling

33.1545

3.11034

 

60

 

Total

33.3043

3.55820

 

120

BDI-II (post)

Reiki

33.5409

5.16071

 

60

 

Counselling

31.7497

4.88970

 

60

 

Total

32.6453

5.08602

 

120

 

Mauchly`s Test ofSphericity

Within Subjects

Effect            Mauchly`sW

Approx. Chi-

Square

 

 

df

 

 

Sig.

TIME

1.000

.000

0

.

         

 

Levene`s Test of Equality of Error Variances

F

df1

df2

Sig.

BDI-II (pre)

2.61

1

118

.141

BDI-II (post)

.494

1

118

.484

Tests the null hypothesis that the error variance of the dependent variable is equal across groups

Measure: MEASURE_1


Tests of Within-Subjects Effects

 

Type III Sum

Source                                                             of Squares

 

df

 

Mean Square

 

F

 

Sig.

TIME

Sphericity Assumed

26.052

1

26.052

3.671

.058

Greenhouse-Geisser

26.052

1.000

26.052

3.671

.058

Huynh-Feldt

26.052

1.000

26.052

3.671

.058

Lower-bound

26.052

1.000

26.052

3.671

.058

TIME * Intervention

Sphericity Assumed

33.377

1

33.377

4.703

.032

Greenhouse-Geisser

33.377

1.000

33.377

4.703

.032

Huynh-Feldt

33.377

1.000

33.377

4.703

.032

Lower-bound

33.377

1.000

33.377

4.703

.032

Error(TIME)

Sphericity Assumed

837.378

118

7.096

 

 

Greenhouse-Geisser

837.378

118.000

7.096

 

 

Huynh-Feldt

837.378

118.000

7.096

 

 

Lower-bound

837.378

118.000

7.096

 

 

Tests of Between-Subjects Effects

Measure: MEASURE_1 Transformed Variable: Average

Type III Sum

Source             of Squares

 

df

 

Mean Square

 

F

 

Sig.

Intercept

260960.845

1

260960.845

8439.889

.000

Intervention

65.567

1

65.567

2.121

.148

Error

3648.553

118

30.920

 

 

 

 

 

T-Test

Paired Samples Statistics

 

Intervention                                            Mean

 

N

Std.

Deviation

 

Std. Error Mean

Reiki             Pair 1

BDI-II (pre)

33.4540

60

3.97698

.51343

BDI-II (post)

33.5409

60

5.16071

.66625

Counselling Pair 1

BDI-II (pre)

33.1545

60

3.11034

.40154

BDI-II (post)

31.7497

60

4.88970

.63126

 

Intervention                                                                    Mean

Std.

Deviation

 

t

 

df

 

Sig. (2-tailed)

Reiki                Pair 1      BDI-II (pre) - BDI-II (post)

-.0869

3.608

-.187

59

.853

Counselling     Pair 1      BDI-II (pre)- BDI-II (post

1.40480

3.920

2.776

59

.007

 
 

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