Opinion and answer of module 4,2

Re:Module 4 DQ 2

 

Consider Mary's experiment regarding whether learning of 6th graders on a math lesson is affected by background noise level. Mary has collected her data.

What is the null hypothesis for her study? When exposed to high levels of background noise, there is no discernable difference in the ability for 6th grade students to learn a math lesson.

What is the alternative hypothesis for her study? When exposed to high levels of background noise, there is a discernable difference in the 6th grade students’ ability to learn a math lesson.

What are the assumptions that must be met about her data before she can correctly use an independent t-test to test the hypotheses? Why? Mary would have make sure that the parameter mean is known for the population before administering the test with the high level of noise This would be important to determine if the noise level had any effect on the population (Gravetter & Wallnau, 2010).

How would she see if her data meet these assumptions?  Mary should also check the results of her hypothesis test using a report of effect size such as Cohen’s d. This would allow for using the mean for the treated sample and the standard deviation as estimates for unknown parameters.

How much room does she have to violate any of these assumptions and still get accurate results from the t-test? Explain and support your answers. Mary should expect a d = 0.5 which corresponds to a medium effect (Gravetter & Wallnau, 2010).  This way she will know if the high level of background noise really is the reason for the change in test scores, of if it is just an anomaly based on the sample.

Maureen

Gravetter, F. J., & Wallnau, L. B. (2010). Statistics for the behavioral sciences (9th ed.). Belmont, CA: Wadsworth Cengage Learning.

 

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