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f. The equation of the linear regression line is: + (Please show your answers to two decimal places) 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. O As x goes up, y goes up. The slope has no practical meaning since you cannot predict a women's weight.

f. The equation of the linear regression line is: + (Please show your answers to two decimal places) 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. O As x goes up, y goes up. The slope has no practical meaning since you cannot predict a women's weight.

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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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 = 0.84 b. The null and alternative hypotheses for correlation are: Ho: P = 0 H₁: p0 The p-value is: 0.00861 (Round to four decimal places) 80 F3 > 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. 34 109 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 a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. d. ² = 0.71 (Round to two decimal places) -59 There is statistically significant evidence conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. 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%. f. The equation of the linear regression line is: $ F4 56 32 140 116 O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O 71% of all women will have the average weight. 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. do Round to 2 decimal places. % F5 (Please show your answers to two decimal places) F6 & 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 = 0.84 b. The null and alternative hypotheses for correlation are: Ho: P = 0 H₁: p0 The p-value is: 0.00861 (Round to four decimal places) 80 F3 > 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. 34 109 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 a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. d. ² = 0.71 (Round to two decimal places) -59 There is statistically significant evidence conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. 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%. f. The equation of the linear regression line is: $ F4 56 32 140 116 O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O 71% of all women will have the average weight. 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. do Round to 2 decimal places. % F5 (Please show your answers to two decimal places) F6 & F7 DII F8 F9
s N F2 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 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. ²0.71 (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%. #3 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. 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 = g. Use the model to predict the weight of a woman who spends 45 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 0.64 additional pounds. 80 F3 O 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. O If a woman does not spend any time talking on the phone, then that woman will weigh 93 pounds. $ (Please show your answers to two decimal places) 4 8888 F4 R % 5 F5 T A 6 F6 Y & 7 AA F7 U * 8 DII F8 ( 9 DD F9 ) 0 J F10 O P C
Transcribed Image Text:s N F2 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 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. ²0.71 (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%. #3 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. 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 = g. Use the model to predict the weight of a woman who spends 45 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 0.64 additional pounds. 80 F3 O 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. O If a woman does not spend any time talking on the phone, then that woman will weigh 93 pounds. $ (Please show your answers to two decimal places) 4 8888 F4 R % 5 F5 T A 6 F6 Y & 7 AA F7 U * 8 DII F8 ( 9 DD F9 ) 0 J F10 O P C
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