W7-DQ

· Write a post of 1 to 2 paragraphs.

· In Module One, complete your initial post by Thursday at 11:59 p.m. Eastern.

· In Modules Two through Ten, complete your initial post by Thursday at 11:59 p.m. of your local time zone.

· Consider content from other parts of the course where appropriate. Use proper citation methods for your discipline when referencing scholarly or popular sources.

Create an example of a research design that would call for repeated measures ANOVA. Be sure to describe the research question, the independent variable(s), the levels of the independent variable(s), and the dependent variables. In your discussion, mention ways that the research question could have been answered using a between-subjects design. When responding to your classmates, provide your perspective on repeated measures designs and discuss other research designs that could have been used to answer the research question.

Classmate1-DC

Hey y’all. Hope your week is going well. 

A good example for this would be a study centered around test environments. The question would be ‘does the environment that a student takes a test affect their performance?’. In this case, the independent variable would be environment and the dependent variable would be testing performance. The different levels would be the different environments; like in a classroom, a gym, or outside. Those three environments would be the different levels.  

The research question could easily be answered with a between-subjects design because it would be comparing the means of three different environments on average test scores.  

Classmate2-GF

Fields (2017) describes repeated measures as residuals that are affected by both between-participant factors and within-participant factors. A research question that would call for repeated measures of ANOVA would be testing if different types of caffeinated beverages have different effects on levels of wakefulness. The independent variable would be the type of caffeinated beverage while the dependent variable would be the participants' wakefulness rating. The levels would be the different types of caffeinated beverages: espresso, cappuccino, and lattes. The overall variance in levels of wakefulness will be caused by individual differences in caffeine tolerance and the amount of caffeine in each beverage. 

Between-subjects design can be used when different treatment conditions utilize different people and so the resulting data are independent (Fields, 2017). The research question could be answered using a between-subject design by calculating the variance of the differences between the 3 different conditions (espresso, cappuccino, latte). This is known as the assumption of sphericity, which assumes that “the variation within conditions is similar and that no two conditions are any more dependent than any other two” (Fields, 2017, p. 481). 

References

Field, A. (2017). Discovering Statistics Using IBM SPSS Statistics (5th ed). SAGE Publications.  https://mbsdirect.vitalsource.com/books/9781526440310