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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 8 women are shown in the table below. Time 18 88 21 Pounds 98 141 119 = 0 65 33 144 101 = 34 56 109 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? H₁: ?0 The p-value is: 32 140 116 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 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. 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. (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 71%. O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. 071% of all women will have the average weight. O There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent 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 8 women are shown in the table below. Time 18 88 21 Pounds 98 141 119 = 0 65 33 144 101 = 34 56 109 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? H₁: ?0 The p-value is: 32 140 116 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 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. 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. (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 71%. O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. 071% of all women will have the average weight. O There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone.

Algebra: Structure And Method, Book 1
Algebra: Structure And Method, Book 1
(REV)00th Edition
ISBN:9780395977224
Author:Richard G. Brown, Mary P. Dolciani, Robert H. Sorgenfrey, William L. Cole
Publisher:Richard G. Brown, Mary P. Dolciani, Robert H. Sorgenfrey, William L. Cole
Chapter12: Quadratic Functions
Section12.8: Joint And Combined Variation
Problem 4P
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# d. ² = 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. (Round to two decimal places) 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 71%. O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O71% of all women will have the average weight. O There is a 71% 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 = 80 F3 + g. Use the model to predict the weight of a woman who spends 45 minutes on the phone. (Please round your answer to the nearest whole number.) Weight = 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 0.64 additional pounds. (Please show your answers to two decimal places) 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 best prediction for the weight of a woman who does not spend any time talking on the phone is 93 pounds. O The y-intercept has no practical meaning for this study. O The average woman's weight is predicted to be 93. Olf a woman does not spend any time talking on the phone, then that woman will weigh 93 pounds. 000 000 F4 do % F5 < MacBook Air F6 & F7 * DII F8 DD F9
Transcribed Image Text:# d. ² = 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. (Round to two decimal places) 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 71%. O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O71% of all women will have the average weight. O There is a 71% 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 = 80 F3 + g. Use the model to predict the weight of a woman who spends 45 minutes on the phone. (Please round your answer to the nearest whole number.) Weight = 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 0.64 additional pounds. (Please show your answers to two decimal places) 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 best prediction for the weight of a woman who does not spend any time talking on the phone is 93 pounds. O The y-intercept has no practical meaning for this study. O The average woman's weight is predicted to be 93. Olf a woman does not spend any time talking on the phone, then that woman will weigh 93 pounds. 000 000 F4 do % F5 < MacBook Air F6 & F7 * DII F8 DD F9
Question 3 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 18 88 21 65 33 Pounds 98 141 119 144 101 < a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? 0 H₁: ?0 The p-value is: 80 F3 (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. 34 56 109 140 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 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 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. ²2 = (Round to two decimal places) 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 71%. 200 F4 32 116 O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. 071% of all women will have the average weight. O There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. % Round to 2 decimal places. F5 A F6 MacBook Air & F7 - * DII F8 F9
Transcribed Image Text:Question 3 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 18 88 21 65 33 Pounds 98 141 119 144 101 < a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? 0 H₁: ?0 The p-value is: 80 F3 (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. 34 56 109 140 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 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 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. ²2 = (Round to two decimal places) 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 71%. 200 F4 32 116 O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. 071% of all women will have the average weight. O There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. % Round to 2 decimal places. F5 A F6 MacBook Air & F7 - * DII F8 F9
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