Sampling Technique:


For our study, we created 120 surveys and sent them out to students. To select students, minitab was used to randomly select 120 students from a list of all students at North Olmsted High School. Surveys were passed out during the students study hall. When we recieved the surveys back, we entered their data into minitab and created a hypothesis test.

 The Survey:

1.Do you or did you participate in North Olmsted High School athletics during this year (Varsity, Junior Varsity, Freshman, or Intramurals)?    

Y          N

If so, what sport/sports did/do you participate in?

________________________________

2.What was you High School GPA during the first semester of this year?

___________________________

3.Are you eligible to participate in a sport at North Olmsted High School?              Y          N

If not, would you participate in a sport

if you were eligible?        Y          N






















The Study:

For out hypothesis test, we chose a 2-Sample T-Test because we compared two sample means for the GPAs of students participating in athletics and students not participating in athletics. We conducted an observational study.

 

µ1 = The true average GPA of students at North Olmsted High School who participate in Athletics.

µ2 = The true average GPA of students at North Olmsted High School who do not participate in Athletics.

Null Hypothesis:
Ho: µ1 - µ2 = 0

Alternative Hypothesis:
Ha: µ1 - µ2 > 0

Level of Significance:
alpha = .05

Assumptions:
This test is a simple random sample. The sample size for yes is 42 and for no is 29. The Central Limit theorem applies for the Yes column, but not for the No column. A boxplot of the No column shows it to be normally distributed so Yes and No columns are normally distributed. This boxplot can be found on the Graphs page.

Test Statistic: 2-Sample T-Test


Results from the TI-84 2-SampTTest:
µ1 > µ2
t = 2.619630798
p = .0059743963
df = 45.10930619

p-value:
p = .0059743963

Data

Graphs