In a study reported in Computers in Human Behavior ("Facebook and Academic Performance", 2010), researchers investigated the relationship between college GPA and Facebook use. One question the researchers were hoping to answer was whether the "average" college GPA for students who use Facebook is lower than the "average" college GPA for students who do not use Facebook. Two samples (141 students who were Facebook users and 68 students who were not Facebook users) were independently selected from students at a large, public Midwestern university. The data in the facebook data set are not exactly the same as in the article, but are very similar. Use the data in this data set to answer the following questions.

13. (2 points) Regardless to your answer to #12b above, run the code in R to obtain the t statistic and p-value. Report the t-statistic with degrees of freedom and the p-value here.

*I ran a "less" conf.level = 0.95.....

"less" conf.level = 0.95

data: GPA by user

t = 6.9847, df = 158.03, p-value = 1

alternative hypothesis: true difference in means between group No and group Yes is less than 0

95 percent confidence interval:

-Inf 0.6657149

sample estimates: mean in group No mean in group Yes

3.623824 3.085603

And also ran a "two.sided" conf.level = 0.95

data: GPA by user

t = 6.9847, df = 158.03, p-value = 7.492e-11

alternative hypothesis: true difference in means between group No and group Yes is not equal to 0

95 percent confidence interval:

0.3860271 0.6904143

sample estimates:

mean in group No mean in group Yes

3.623824 3.085603

I am confused by the question 13. above. Which t-statistic with degrees of freedom and the p-value should I use?

12. Obtain and include a properly labeled side-by-side box-and-whisker plot that shows the comparison of college GPAs between Facebook users and non-Facebook users in the sample. a. (1 point) Include the properly labeled graph here. b. (2 points)ls it appropriate to use the t-methods in this problem? Briefly explain. c. (2 points) Do you feel the null hypothesis will be rejected based on your graphical display? Why or why not? Two-sample t-test and confidence interval for difference in population means R code t.test(yyy ~ xxx, data=zzz, mu = mmm, alternative = \"aaa", conf.level = ccc) Replace zzz with the name of the data set Replace yyy with the name of the response variable Replace xxx with the name of the explanatory variable Replace mmm with the hypothesized value for the difference in population means (which will always be @ for our purposes). The default is @, 000 b o Replace aaa with either \"less, \"greater\