Statistics-QA167

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Assignment
 
The SPSS data files for questions 2 and 3 of this assignment are available on Blackboard Learn

 

1.A group of researchers are interested in the idea that pathogen (disease) disgust is linked to political conservatism. They design a study in which participants are randomly designed to view either images that are not particularly relevant to disease risk, such as wasps and healthy limbs, or images that are relevant to disease risk, such as fleas and limbs with infected wounds.  After viewing the images, participants fill out a questionnaire about their political views. High scores on the questionnaire indicate that the participant is politically conservative. Scores for the two groups are shown below.
 

Conservatism in the low-disease relevance group Conservatism in the high-disease relevance group
7.32 5.02
4.73 1.96
.33 6.14
7.02 5.12
8.95 7.67
4.31 6.04
5.26 5.83
4.84 6.19
3.68 6.93
4.97 .65

 

  1. What is the null hypothesis in this experiment?
  2. Suppose that the researchers’ hypothesis is that conservatism scores will be higher after viewing disease-relevant images than after viewing less disease-relevant images. What would be an appropriate statistical test for this hypothesis? Should they use a one-tail or a two-tail test?
  3. Enter this data into SPSS, being careful to consider whether it is between-groups or within-group design. Perform the analysis you have described in part b. Present your results appropriately for inclusion in a results section of a scientific report.

 

Suppose now that the researchers hypothesise that only images that depict humans are likely to have an effect on political views. They define a third experimental condition in which participants view only images that contains disease-relevant depictions of humans. This condition contains pictures of, for example, infected (human) wounds, but not fleas.

Group 1: Conservatism in the low-disease relevance group Group 2: Conservatism in the high-disease relevance group Group 3: Conservatism in the human/high-disease relevance group
7.32 5.02 4.47
4.73 1.96 4.42
.33 6.14 4.19
7.02 5.12 3.79
8.95 7.67 3.11
4.31 6.04 5.53
5.26 5.83 2.59
4.84 6.19 7.11
3.68 6.93 5.43
4.97 .65 5.82

 

    d)

  1. The researchers use ANOVA to analyse this data. They want to compare conservatism scores after viewing low disease-relevant images with scores after viewing high disease-relevant images (group 1 vs group 2), and also to compare conservatism scores after viewing low disease-relevant images with scores after viewing human-only high disease-relevant images (group 2 vs group 3). This time, they simply hypothesise that scores will differ between these groups, and do not make specific predictions about whether they will increase or decrease. What is the name for the planned contrasts they should choose in SPSS? Should they use one-tail or two-tail interpretation of the results?
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    e)

  1. Is there evidence of a significant overall effect of image type on conservatism scores? Is there evidence of a significant difference between groups 1 and 2? Is there evidence of a significant difference between groups 1 and 3? State the appropriate statistics to justify your answer in each case.

 

    f)

  1. Is there evidence of a violation of the assumption of homogeneity of variance? State the appropriate statistics to justify your answer.

 

    g)

  1. Create a bar graph to display this data, including all the required elements for publication in a scientific report.

 

  1. Ask people to perform a task for which they measure response time, and also ask them about their age and the amount of sleep they had last night. The researchers enter this data into an SPSS datafile, with each row representing a person, and the columns representing their age, their sleep from last night, and their response time. Response time is coded so that a higher score indicates a faster response. This data is available in a file called “Exceptional Question 2 data.sav” on Blackboard.

 

    a)

  1. Using this data, create a scatter graph of the relationship between sleep and response times, making sure to include all the elements appropriate to a scientific publication.

 

    b)

  1. Form looking at this graph, would you hypothesise that there is a significant                     relationship between hours of sleep and response times?

 

    c)

  1. What is the statistical correlation between hours of sleep and response times in this sample? What about between age and response times? Report your analysis, with statistics, in a way that is suitable for a scientific report,

 

    d)

  1. The researchers hypothesise that the apparent effects of sleep on response times might be due to the effects of age on both response times and sleep. They hypothesise that 1) age will be negatively related to hours of sleep, and hence that 2) after controlling for age, there will be no relationship between sleep and response times.

 

To test their first hypothesis, they perform a linear regression, to explore the relationship between age and sleep. Perform a linear regression yourself, and report the results in full. Include a sentence, in plain English, to describe the relationship between age and sleep time.

     

  1. The people in the sample are all aged between 19 and 51. Use the output of your regression to estimate what the average amount of sleep would be for a 64 year old.
  2. Perform a hierarchical linear regression to test whether sleep predicts response time after controlling for age. Is sleep a predictor of response time when age is included in the model, and if so, does it explain a large amount of variation? Write your results in full.

 

     

  1. Some researchers are interested in whether physical exercise influences mood, and whether the effects are of similar size for men and women. To test this hypothesis they randomly allocate participants to either go for a run or sit still for 10 minutes. Afterwards they ask people to complete a standard mood questionnaire, in which high scores indicate positive mood. The researchers enter this data into an SPSS data file, with each row representing a participant, and three columns representing their sex, whether they went for a run or sat still, and their score on the mood questionnaire. This data is available in a file called “Exceptional Question 3 data.sav” on Blackboard.
       
      a)

    1. Perform an analysis to test the researchers’ hypotheses, including all the required follow up tests and descriptive that you believe are necessary. Write up this analysis in full, describing any statistical assumptions that you think are necessary, or explaining why you think that such tests are not necessary.

 

    b)

  1. Produce an appropriate graph to show your findings.

 
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