1. Using the MM207 Student Data Set:
a) What is the correlation between student cumulative GPA and the number of hours spent on school work each week? Be sure to include the computations or StatCrunch output to support your answer. ANSWER: Correlation: 0.30790085
Correlation between Q10 What is your cumulative Grade Point Average at Kaplan University? And Q11 How many hours do you spend on school work each week? Is: Correlation: 0.30790085
b) Is the correlation what you expected?
The correlation caught me by surprise. I was expecting the correlation to be much higher because it has been generally known that the more hours you study, the better grades you get, thus the higher your overall GPA is.
c) Does the number of hours spent on school work have a causal relationship with the GPA? ANSWER: There is a casual relationship
Looking at the scatter plot below, you can assume that there is a casual relationship between the two variables regardless of their low correlation. [pic]
d) What would be the predicted GPA for a student who spends 16 hours per week on school work? Be sure to include the computations or StatCrunch output to support your prediction. ANSWER: Predicted GPA = 3.45
2. Using the MM207 Student Data Set:
a) Select a continuous variable that you suspect would not follow a normal distribution. ANSWER: Continuous Variable: Age
b) Create a graph for the variable you have selected to show its distribution. ANSWER:
c) Explain why these data might not be normally distributed. ANSWER:
The reason why I chose age as an irregular distributed variable is because there are all different age groups that still study today. As online is getting more and more practical for students, individuals that are older are taking advantage...