PLEASE WRITE AT LEAST 200 WORDS PER QUESTION UTILIZING AT LEAST 2 SOURCES FOR QUESTIONS 1 & 2 AND AT LEAST 1 SOURCE FOR QUESTIONS 3 & 4. PLEASE LIST THE RELEVANT SOURCES BENEATH EACH APPROPRIATE QUESTION – NOT ALL LISTED AT THE END. THANK YOU._x000D_
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Question 1. (2 Sources) In Module 4, we considered Mary’s interest in doing a study to see if learning of 6th graders on a math lesson is affected by background noise level. There, she was planning to use two noise conditions and then analyze her outcomes using a t-test for independent groups. Describe the study Mary might plan where she would use a one-way analysis of variance (ANOVA) for independent groups instead of a t-test to study differences between noise levels. What is her independent variable here? Describe the conditions she could create for this study. What is her dependent variable? Describe a way to measure the DV so that each participant would have one score at the end that would be on a continuous scale of measurement. Support your responses. (For reference, Question from Module 4: Mary is planning a study to see if learning of 6th graders on a math lesson is affected by background noise level. She wants to use a t-test for independent groups to analyze her results. Help her plan her study. What is her independent variable (IV) here? Describe two conditions she could create for the IV in her study. What is her dependent variable (DV) here? Describe a way to measure the DV so that each participant would have one score at the end. Would this DV measure be on a continuous scale of measurement? Why is this important? Explain and justify.)_x000D_
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Question 2: (2 Sources) Consider Mary’s study of whether the learning of 6th graders on a math lesson is affected by background noise level. Describe the pros and cons of Mary using a repeated measures design for this study. What would you probably choose to do? Support your responses._x000D_
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Question 3: (1 Source) Compare and contrast the analysis of variance (ANOVA) test with the t-test._x000D_
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Question 4: (1 Source) Compare and contrast repeated-measures ANOVAs with two-factor ANOVAs.