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 9 women are shown in the table below. Time 86 90 61 41 66 28 75 10 67 Pounds 150 164 122 116 133 116 132 111 144 a. Find the correlation coefficient: Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: 2 7 = 0 HI : 7 7 7 0 The p-value is: (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. 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. 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 there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. 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. d. 72 = (Round to two decimal places) e. Interpret r2 : Given any group of women who all weight the same amount, 78% of all of these women will weigh the predicted amount. 78% of all women will have the average weight. 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 78%. There is a 78% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. f. The equation of the linear regression line is: y = +(Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 43 minutes on the phone. Weight = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: As x goes up, y goes up. The slope has no practical meaning since you cannot predict a women's weight. For every additional minute women spend on the phone, they tend to weigh on averge 0.59 additional pounds. i. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. The average woman's weight is predicted to be 98. The best prediction for the weight of a woman who does not spend any time talking on the phone is 98 pounds. if a woman does not spend any time talking on the phone, then that woman will weigh 98