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 8 women are shown in the table below. Time Pounds 57 16 63 63 56 59 55 75 149 120 172 158 158 148 160 172 a. Find the correlation coefficient: 7' = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: H0: = 0 H13 7e 0 The p-value is: [3 (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. 0 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. 0 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. 0 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. O 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. d. 7'2 = C] (Round to two decimal places) e. Interpret 7'2 : O 84% of all women will have the average weight. 0 There is a 84% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. Q 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 84%. 0 Given any group of women who all weight the same amount, 84% of all of these women will weigh the predicted amount. Show All X heequation of the linear regression line is: y=:]+ Sac (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 57 minutes on the phone. Weight = C] (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: 0 For every additional minute women spend on the phone, they tend to weigh on averge 0.88 additional pounds. 0 The slope has no practical meaning since you cannot predict a women's weight. 0 As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: 0 The y-intercept has no practical meaning for this study. 0 The average woman's weight is predicted to be 106. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 106 pounds. 0 If a woman does not spend any time talking on the phone, then that woman will weigh 106 pounds