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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 42 22 58 33 24 74 15 Pounds 138 119|| 179| 155 113 211 122 a. Find the correlation coefficient: r b. The null and alternative hypotheses for correlation are: Ho:[ H₁: #0 The p-value is: Round to 2 decimal places. (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 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. 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.

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 42 22 58 33 24 74 15 Pounds 138 119|| 179| 155 113 211 122 a. Find the correlation coefficient: r b. The null and alternative hypotheses for correlation are: Ho:[ H₁: #0 The p-value is: Round to 2 decimal places. (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 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. 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.

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 42 22 58 33 24 74 15 Pounds 138 119 179 155 113 211 122 a. Find the correlation coefficient: r=| b. The null and alternative hypotheses for correlation are: Ho: ? ✓=0 H₁ : ? ✓ #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. Round to 2 decimal places. 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 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. 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. 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. a. The equation of the linear regression line is: ŷ = + I (Please show your answers to two decimal places) b. Use the model to predict the weight of a woman who spends 4 minutes on the phone. Weight = c. 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 1.61 additional pounds. The slope has no practical meaning since you cannot predict a women's weight. As x goes up, y goes up. d. 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 87 pounds. The y-intercept has no practical meaning for this study. The average woman's weight is predicted to be 87. The best prediction for the weight of a woman who does not spend any time talking on the phone is 87 pounds.
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 42 22 58 33 24 74 15 Pounds 138 119 179 155 113 211 122 a. Find the correlation coefficient: r=| b. The null and alternative hypotheses for correlation are: Ho: ? ✓=0 H₁ : ? ✓ #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. Round to 2 decimal places. 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 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. 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. 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. a. The equation of the linear regression line is: ŷ = + I (Please show your answers to two decimal places) b. Use the model to predict the weight of a woman who spends 4 minutes on the phone. Weight = c. 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 1.61 additional pounds. The slope has no practical meaning since you cannot predict a women's weight. As x goes up, y goes up. d. 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 87 pounds. The y-intercept has no practical meaning for this study. The average woman's weight is predicted to be 87. The best prediction for the weight of a woman who does not spend any time talking on the phone is 87 pounds.
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