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

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: Correlation: 0.30790085

b) Is the correlation what you expected?

ANSWER:

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

From StatCrunch:

[pic]

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:

[pic]

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 of graduating and studying collegiately.

d) Select a second continuous variable that you believe would approximate a normal distribution ANSWER: Height

e) Create a graph to show its distribution.

ANSWER:

[pic]

f) Explain why these data might be normally distributed.

.ANSWER:

Initially, I thought that height would not have a great deal of frequency. I was proven otherwise when I created the frequency chart for all the heights. As you can see, larger heights are more compacted together in the middle near the mean.

3. Jonathan is a 42 year old male student and Mary is a 37 year old female student thinking about taking this class. Based on their relative position, which student would be farther away from the average age of their gender group based on this sample of MM207 students? ANSWER: Johnathan

From StatCrunch:

[pic]

4. If you were to randomly select a student from the set of students who have completed the survey, what is the probability that you would select a male? Explain your answer. ANSWER: Probability: 0.165 Converted to a Percentage of 16.5% Females: 85

Males: 17

Didn’t Answer: 1

Total # of Students: 103

Formula Used:

(total # of males) / (total # of students (M & F) + total # unanswered) = Probability of Males

Plugging in Numbers:

17 / (102 + 1) ( 0.165 *(Rounded to the nearest thousandth)

Converted to a percentage of 16.5%

From StatCrunch:

[pic]

5. Using the sample of MM207 students:

a) What is the probability of randomly selecting a person who is conservative and then selecting from that group someone who is a nursing major? ANSWER:

Total # of Students that answered:

Conservative ( 26%Conservative Nursing ( 11%

Total # of Students (including those that didn’t answer):

Conservative ( 25%Conservative Nursing ( 11%

* Based on the 99 students that answered the question:

Conservative: 26/99 = 0.2626 ( 26% (rounded to the...