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A researcher wishes to know whether different pacing strategies affect time to complete a marathon.

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A researcher wishes to know whether different pacing strategies affect time to complete a marathon. The researcher randomly assigns a group of volunteers to either a group that (a) starts slow and then increases their speed (slow-start group), (b) starts fast and slows down

(fast-start group), or (c) runs at a steady pace throughout (steady-pace group). The number of

hours to complete the marathon is the outcome (dependent) variable. There are 30 participants in each group. In the data set, the “time” variable indicates the hours taken to complete the

marathon (the “self-efficacy” variable will not be used until Section 3). In the “group” variable, 1 indicates the slow-start group, 2 indicates the fast-start group, and 3 indicates the steady-pace

group.

 

1. Please submit your jamovi dataset file with your analyses saved. (5 points)

 

2. What is the null hypothesis for the analysis? (5 points)

 

3. What is the alternative hypothesis for the analysis? (5 points)

 

4. Plot a histogram of the “time” variable for each group separately (it means that you should provide three histograms). You can paste the screenshots of the plots from jamovi here. (3 points)

 

5. Please report the skewness and kurtosis of the “time” variable for the steady-pace group exactly as they appear on the jamovi printout. (4 points)

 

6. Please report the variance of the “time” variable for the fast-start group exactly as it

appears on the jamovi printout (2 points). Interpret this variance value using your own words (3 points).

 

7. Please perform the correct test and provide the F-statistic exactly as it appears on the jamovi printout. (3 points)

 

8. Please interpret the F-statistic in Q7 using your own words. (5 points)

 

9. Please provide the value that captures the between group differences on a squared metric. Provide it exactly as it appears on the jamovi printout. (3 points)

 

10. Please provide the value that captures the naturally occurring score differences within groups on a squared metric. Provide it exactly as it appears on the jamovi printout. (3 points)

 

11. Please interpret the probability value (p value) for this F-test. I am not asking whether

the result is significant or whether the p value is smaller than 0.05. My question is asking you to conceptually interpret this probability using your own words. (5 points)

 

12. What is the value of the effect size in this study? Provide the value exactly as it appears on the jamovi printout. (3 points)

 

13. Based on the benchmarks for this type of effect size, is the effect size negligible, small, medium, or large (3 points)?

 

14. How can the effect size in Q13 be conceptually understood (i.e., what is its interpretation)? (5 points)

 

15. Based on the results in Q8 and Q11, can you conduct post-hoc comparisons? If you can, what do you find? If you find evidence that two groups are different from each other,

please state which group has a higher mean when comparing the two groups. (5 points)

 

16. Please provide an APA-style summary for your analysis results. Note that you should include the following results 1) descriptive statistics table, 2) F statistic, 3) degrees of

freedom, 4) p value, 5) effect size, its magnitude (i.e., negligible, small, medium, or large) and its interpretation, and 6) follow-up tests with their p values only if you need to conduct follow-up tests. You should also interpret your results (e.g. whether tests are significant; what the significant or nonsignificant results indicate). Please create the

descriptive statistics table by yourselves (e.g., using Word, Excel, etc.) instead of just copying and pasting a table from jamovi. Just listing your numeric results or pasting a screenshot of the jamovi output will lead to losing points. (11 points)

 

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