A quick review of how to complete the course. Watch the Attend. Read the Chapter. Go to Dr. Mâ€™s website (http://www.drjimmirabella.
INTERPRET THE RESULTS. This one is NOT the same as reporting the results. No, NO, NO! Here you are going to explain what the results are telling us. What do they MEAN? What conclusions can we draw from the results? This is a critical part of the answer EVERY TIME! That’s because the point of the class is to make sure you can USE statistics. You show you can use them by (being able to explain why you use them in A above) being able to EXPLAIN what the results MEAN – that’s more than just reading the numbers that Excel spits out. For example, let’s say the results of your analysis say that there is a statistically significant difference between the GPAs of males versus females. If you say “I accept the alternative hypothesis that GPAs are different for males and females” that is NOT a good answer! All that answer did was restate the results. You MUST go on and explain what that result MEANS – INTERPRET it for me based on the information you have. So you might go on and say something like, “males tend to have higher GPAs than females. This may be true because males tend to work fewer hours than females and therefore they have more time to study.” That’s an interpretation – it may take a little creativity and it will take a reading of the chapter and watching the Attend as well as knowing your dataset. (And by the way, I made that up – that result or interpretation is not necessarily true!!
Be very careful about copying and pasting in the spreadsheets. If you copy and paste cells from one spreadsheet to another you WILL end up with wrong answers! Dr. M has a lot of equations that are “hidden” that you will lose if you just copy and paste cells.
1.The battle of the sexes lives on still today. Since admission standards do not address gender whatsoever, there should be an equally diverse group of men and women in school, but do they perform equally well. Using the sample of 200 students, conduct a hypothesis test for two independent samples to determine if the mean GPA differs for men and women. Use a .05 significance level
2.Can a student keep up their grade performance at the next level? Is a strong GPA at the Bachelors level a good predictor of a strong GPA at the Masters level, or are GPAs naturally going to decline since graduate school is tougher, or will GPAs automatically be higher in graduate school because of the 3.00 requirement to graduate and the treatment of a C as subpar instead of average? Using the sample of 200 students (in the data file), conduct a hypothesis test for paired samples and test if there is a difference in the mean GPA from the Bachelors to the Masters programs. Use a .05 significance level.
3.Given the reasons why people get their Masters, you surmise that men are more likely to declare a major than women. Using the sample of 200 students (in the data file), conduct a hypothesis test of proportions to determine if the proportion of women with “no major” is greater than the proportion of men with “no major”. Use a .05 significance level.
4.You have probably heard that if you want something done, give it to a busy person. So is one’s employment status a factor in their academic performance? Using the sample of 200 students (in the data file), conduct a hypothesis test using Analysis of Variance to determine if there is a difference in the mean GPA for those who are unemployed vs. work part-time vs. work full-time.