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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 28 26 52 36 51 Pounds 138 123 157 139 175 66 172 42 138 Round to 2 decimal places. a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: H₂: ?v=0 H₁:20 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 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 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 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.

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 28 26 52 36 51 Pounds 138 123 157 139 175 66 172 42 138 Round to 2 decimal places. a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: H₂: ?v=0 H₁:20 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 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 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 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.

Algebra and Trigonometry (MindTap Course List)
Algebra and Trigonometry (MindTap Course List)
4th Edition
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section1.FOM: Focus On Modeling: Fitting Lines To Data
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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 28 26 52 Pounds 138 123 157 139 = 0 36 51 175 #0 66 172 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: 2 H₁: The p-value is: 42 138 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. 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. 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 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. (Round to two decimal places) d. ² = e. Interpret ²: 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 79%. O 79% of all women will have the average weight. There is a 79% 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: ŷ= O Given any group of women who all weight the same amount, 79% of all of these women will weigh the predicted amount. z (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 56 minutes on the phone. Weight= (Please round your answer to the nearest whole number.)
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 28 26 52 Pounds 138 123 157 139 = 0 36 51 175 #0 66 172 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: 2 H₁: The p-value is: 42 138 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. 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. 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 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. (Round to two decimal places) d. ² = e. Interpret ²: 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 79%. O 79% of all women will have the average weight. There is a 79% 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: ŷ= O Given any group of women who all weight the same amount, 79% of all of these women will weigh the predicted amount. z (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 56 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 1.21 additional pounds. As x goes up, y goes up. O The slope has no practical meaning since you cannot predict a women's weight. i. Interpret the y-intercept in the context of the question: O The average woman's weight is predicted to be 97. O The y-intercept has no practical meaning for this study. O If a woman does not spend any time talking on the phone, then that woman will weigh 97 pounds. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 97 pounds.
Transcribed Image Text: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 1.21 additional pounds. As x goes up, y goes up. O The slope has no practical meaning since you cannot predict a women's weight. i. Interpret the y-intercept in the context of the question: O The average woman's weight is predicted to be 97. O The y-intercept has no practical meaning for this study. O If a woman does not spend any time talking on the phone, then that woman will weigh 97 pounds. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 97 pounds.
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