1. Rebecca Robinson

2.  Listed all public universities in the United States and numbered them.  Used a random number generator to generate 25 random colleges to use for the mean of the United States.  All public universities in Michigan were used, so a random sample was not used.

3.  Public Universities in the United States:  Mean = $16,599  Std. Dev. = $4,780  Public Universities in Michigan:  Mean = $20,140  Std. Dev. = $6,369

4.  Public Universities in the United States:  Mean = 528  Std. Dev. = 65.87  Public Universities in Michigan:  Mean = 575  Std. Dev. = 45.64

5.  H 0 : μ = 0, where μ is the difference between the means of university tuition in the United States and university tuition in Michigan.  H a : μ ≠ 0  t = -2.0085 p-value =.05647  We fail to reject H 0 at the.05 level; since our p- value is greater than.05, the difference between the means of university tuition in the United States and Michigan is not statistically significant.

6.  H 0 : μ = 0, where μ is the difference between the means of math SAT scores of entering freshmen in the United States and Michigan.  H a : μ ≠ 0  t = -2.618 p-value=.0127  We reject H 0 at the.05 level; since our p-value is less than.05, there is evidence that the difference between math SAT scores in the United States and Michigan is statistically significant.

7. There is a moderately weak positive correlation between university out-of-state tuition and math SAT score of the entering freshman. r =.484 r 2 =.234

8.  There is not a significant difference in out-of-state tuition.  However, there is a significant difference in the entering math SAT score. Michigan tended to have higher math SAT scores than colleges in the United States in general.  This could be because of the lack of information of SAT scores for Michigan universities. ACT scores had to be converted into SAT scores for the data, and since the two exams are different, it could account for the significant difference.  Also, university tuition and math SAT scores are not strongly related.