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. My answer :
0.27817234
(from StatCrunch):
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: 0.27817234
b) Is the correlation what you expected? My answer: No. I expected the correlation to be much higher because the more hours you study should equate to a much higher GPA – in theory that is.
c) Does the number of hours spent on school work have a causal relationship with the GPA? My answer: Yes. I was going to say no (because of the low correlation above), until I did a scatter plot. This shows that
MM207 Final Project there definitely is a casual relationship between study time and GPA.
yuck. There are 2 points on the right that most likely could be excluded. 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. My answer: 3.6
from StatCrunch Group by: Q11 How many hours do you spend on school work each week? Q11 How many hours do you spend on school work each week? 3 4 5 6 7 8 10 11
Mean 3.6666667 2 3.3775 3.0714285 3.75 3.352 2.9693334 3.6466668
n 3 1 8 7 2 5 30 3
Variance 0.33333334 NaN 0.3129357 0.42641428 0.125 0.26252 1.6706271 0.14423333
MM207 Final Project
12 13 14 15 16 hours
3.290909 4 3.93 3.7127273 3.6
11 2 2 11 3
1.4214091 0 0.0098 0.11040182 0.07
2.
Select a continuous variable that you suspect would not follow a normal distribution. a) My answer: my continuous variable is “Age” b) Create a graph for the variable you have selected to show its distribution. My answer:
MM207 Final Project a)