A.. 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	12	8	2	1	6	15	13
Score	63	84	85	52	62	62	97	86

1. Find the correlation coefficient: r=__________ Round to 2 decimal places.
2. The null and alternative hypotheses for correlation are: H0: ? r = 0 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. 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 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 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 there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful.
• 4. r2=________ (Round to two decimal places)
• 5. Interpretr2:
• 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.
• 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.
• 82% of all students will receive the average 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%.
• 6. The equation of the linear regression line is: y = ___________ + _____________x (Please show your answers to two decimal places)
• 7 .Use the model to predict the final exam score for a student who spends 11 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: ................ .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 2.48 higher on the final exam.
• As x goes up, y goes up.
• 9. Interpret the y-intercept in the context of the question:

• The y-intercept has no practical meaning for this study.
• If a student does not study at all, then that student will score 56 on the final exam.
• The average final exam score is predicted to be 56.
• The best prediction for a student who doesn't study at all is that the student will score 56 on the final exam.

B. What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 7 women are shown in the table below.

Time	86	60	75	79	43	50	12
Pounds	168	126	149	155	120	144	110

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.

• There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.
• There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.
• There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful.
• There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate.

4. r2=________ (Round to two decimal places)

5. Interpretr2r2:

• Given any group of women who all weight the same amount, 81% of all of these women will weigh the predicted amount.
• There is a 81% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone.
• There is a large variation in women's weight, but if you only look at women with a fixed weight, this variation on average is reduced by 81%.
• 81% of all women will have the average weight.
• 6. The equation of the linear regression line is: y =______ +_______ x (Please show your answers to two decimal places) 7. Use the model to predict the weight of a woman who spends 34 minutes on the phone. Weight = ________ (Please round your answer to the nearest whole number.) 8. Interpret the slope of the regression line in the context of the question:
  • For every additional minute women spend on the phone, they tend to weigh on averge 0.73 additional pounds.
  • As x goes up, y goes up.
  • The slope has no practical meaning since you cannot predict a women's weight.
• 9. Interpret the y-intercept in the context of the question:

• If a woman does not spend any time talking on the phone, then that woman will weigh 97 pounds.
• The best prediction for the weight of a woman who does not spend any time talking on the phone is 97 pounds.
• The y-intercept has no practical meaning for this study.
• The average woman's weight is predicted to be 97.