3. Suppose the linear correlation coefficient for SAT scores as a function of high school GPA is 74%. Use the coefficient of determination to estimate the fraction of the change in SAT scores that can be explained by the change in high school GPA. rounded to three decimal places.

4. Suppose the linear correlation coefficient for SAT scores as a function of high school GPA is 0.71. Use thern>3

rule to determine the smallest sample size we would need in order to be able to say that the correlation between SAT scores and high school GPA is significant (and hence the relationship between the variables is unlikely to be due just to random chance. If the correlation is not significant, some statisticians, when asked to predict the SAT score given the high school GPA of a student, would just report the mean SAT score instead of using the line of best fit to calculate the SAT score). It should be an integer.

5. You have a sample of 30 students and plan to determine if a linear relationship can be used to predict the SAT score as a function of the high school GPA. What value does the correlation coefficient need to exceed, according to thern>3

rule, in order for you to be able to say that the correlation between the SAT score and the high school GPA is significant, instead of it having occurred by random chance? rounded to three decimal places.