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a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? v = 0 H1: ? v + 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. O 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. 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. O There is statisticaly 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 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.

a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? v = 0 H1: ? v + 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. O 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. 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. O There is statisticaly 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 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.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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 14 40 24 76 74 87 84 Pounds 124 122 116 178 181 174 167 a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? ▼ Hj: ? v 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. O 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. 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. O 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. d. r2 (Round to two decimal places) e. Interpret r? : O Given any group of women who all weight the same amount, 86% of all of these women will weigh the predicted amount. O 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 86%. O 86% of all women will have the average weight. O There is a 86% 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: x (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 36 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: O For every additional minute women spend on the phone, they tend to weigh on averge 0.90 additional pounds. O The slope has no practical meaning since you cannot predict a women's weight. O As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: O If a woman does not spend any time talking on the phone, then that woman will weigh 100 pounds. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 100 pounds. The average woman's weight is predicted to be 100. O The y-intercept has no practical meaning for this study.
Transcribed Image Text: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 14 40 24 76 74 87 84 Pounds 124 122 116 178 181 174 167 a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? ▼ Hj: ? v 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. O 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. 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. O 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. d. r2 (Round to two decimal places) e. Interpret r? : O Given any group of women who all weight the same amount, 86% of all of these women will weigh the predicted amount. O 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 86%. O 86% of all women will have the average weight. O There is a 86% 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: x (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 36 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: O For every additional minute women spend on the phone, they tend to weigh on averge 0.90 additional pounds. O The slope has no practical meaning since you cannot predict a women's weight. O As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: O If a woman does not spend any time talking on the phone, then that woman will weigh 100 pounds. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 100 pounds. The average woman's weight is predicted to be 100. O The y-intercept has no practical meaning for this study.
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