What is the relationship between the amount of time statistics students study per week and their final exam scores? The results of the survey are shown below.

Time	0	2	5	1	12	15	8
Score	53	72	80	55	84	100	73

1. Find the correlation coefficient: r=r= Round to 2 decimal places.
2. The null and alternative hypotheses for correlation are: H0:H0: ? r == 0 H1:H1: ? r 0 The p-value is: (Round to four decimal places)
3. Use a level of significance of=0.05=0.05to state the conclusion of the hypothesis test in the context of the study.
4. r2r2= (Round to two decimal places)
5. Interpretr2r2:
6. The equation of the linear regression line is: yy^ = + xx (Please show your answers to two decimal places)
7. Use the model to predict the final exam score for a student who spends 9 hours per week studying. Final exam score = (Please round your answer to the nearest whole number.)
8. Interpret the slope of the regression line in the context of the question:
9. Interpret the y-intercept in the context of the question:
   • The y-intercept has no practical meaning for this study.
   • The best prediction for a student who doesn't study at all is that the student will score 58 on the final exam.
   • If a student does not study at all, then that student will score 58 on the final exam.
   • The average final exam score is predicted to be 58.

• As x goes up, y goes up.
• The slope has no practical meaning since you cannot predict what any individual student will score on the final.
• For every additional hour per week students spend studying, they tend to score on averge 2.59 higher on the final exam.

• Given any group that spends a fixed amount of time studying per week, 82% of all of those students will receive the predicted score on the final exam.
• There is a large variation in the final exam scores that students receive, but if you only look at students who spend a fixed amount of time studying per week, this variation on average is reduced by 82%.
• There is a 82% chance that the regression line will be a good predictor for the final exam score based on the time spent studying.
• 82% of all students will receive the average score on the final exam.

• There is statistically insignificant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the use of the regression line is not appropriate.
• There is statistically significant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful.
• There is statistically insignificant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying.
• There is statistically significant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying.