The Study:

For the study I have obtained a sample of male students from the masterlist of all students in NOHS. For my study, I only used male students for my sample. The sample was randomly selected using Minitab. The sample consisted of 75 male students with a random amount for each grade. A survey was sent out to the study halls of the randomly selected students and were asked to be filled out and returned. Of the 75 people in the sample only 55 responses were able to used. Some had to be discarded due to unclear responses, polaris, and students just not participating.

Copy of Survey:

What is your cumulative G.P.A?

_________________________________________

Do you regularly play videogames?
(at least one hour per day)

_________________________________________

µ₁ = mean G.P.A of people who play videogames regularly

µ₂ =mean G.P.A of people who do not play.

H_o:   µ_{1 -}  µ₂ = 0

H_a:   µ_{1 -}  µ_{2 ≠ 0}

α = .05

Assumptions: The data is independently selected. Assume the data is normally distributed so the CLT applies.

t= -1.12 Df: 50

VVVV Discriptive Data VVVV

Two-Sample T-Test and CI: Cumulative G.P.A (yes), Cumulative G.P.A (no)

Two-sample T for Cumulative G.P.A (yes) vs Cumulative G.P.A (no)

                                 N  Mean StDev SE Mean
Cumulative G.P.A (yes) 23 2.817  0.637    0.13
Cumulative G.P.A (no)  32 3.022  0.711    0.13


Difference = mu (Cumulative G.P.A (yes)) - mu (Cumulative G.P.A (no))
Estimate for difference: -0.205
95% CI for difference: (-0.572, 0.163)
T-Test of difference = 0 (vs not =): T-Value = -1.12 P-Value = 0.268 DF = 50

p-value = 0.268

Conclusion: We fail to reject the null hypothesis at the 0.05 level of significance because the p-values > α. Therefore, there is insufficient evidence to say that the true mean G.P.A of people who play video games is different than the mean G.P.A of those who don’t.