Instructions:
-Use Canadian/US English, make sure your writing is clear and no grammar or punctuation errors
-Answer each discussion question separately
-Provide a response to EACH of the following discussion questions
-Minimum of 225-275 words for each response (for each question)
-Everything must be in YOUR OWN WORDS
1.Sample size can play an important role in gathering and analyzing data. Describe this importance. Can samples of small size still be relevant? Why or why not? What constitutes a “small sample”?
OR
Explain in your own words the “power of a statistical test”. Do you proceed with the test if you don’t have enough “power”? How does the power affect the results of the test?
2.Can statistical analysis be done on distributions that are not “normal”? Explain in detail.
OR
Are all data sets best described with graphs? Talk about when a data set might not benefit from being displayed graphically.
3.Many times, multiple variables can be correlated, affecting the outcome of the dependent variable. Describe, in detail, the process for determining if more than one variable contributes to the outcome of a single dependent variable.
OR
How accurate is a regression analysis and how do you know? What attributes of the analysis will determine whether the analysis is accurate and to what extent? Can inaccurate regression analyses be used to an analyzer’s benefit? Explain in detail.
4.For reference, this is an online statistics course (Undergraduate level). Just come up with something to answer this question: (It can be anything). Your answer can be generic, no need to be too specific.
5.Sometimes it is necessary to compare the means of several variables. When might this be the case? Why?
OR
Comparing two means can be tricky in statistics since usually one of the groups is manipulated in some type of way (i.e., given a placebo). How do statisticians overcome this obstacle to generate good data?
6.There has been a lot of discussion so far about effect size. In your own words, describe what is meant by effect size and why it is important when analyzing data.
OR
What are the pros and cons of using Factorial Designs? What can and should you do to minimize the cons?
7.Talk about factorial designs, repeated measure designs, and mixed design. Explain in your own words the difference between these. Give specific examples for which you would choose one method instead of the others.
OR
Explain in detail a “Goodness-of-Fit” test and when and why this test would be used versus any other analysis test.
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