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. Time87483767423979Pounds194152154171149128198 r2r2 = (Round to two decimal places) Interpret r2r2 : Given any group of women who all weight the same amount, 86% of all of these women will weigh the predicted amount.86% of all women will have the average weight.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.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%.The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the weight of a woman who spends 32 minutes on the phone.Weight = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: For every additional minute women spend on the phone, they tend to weigh on averge 1.15 additional pounds.The slope has no practical meaning since you cannot predict a women's weight.As x goes up, y goes up.Interpret the y-intercept in the context of the question:The best prediction for the weight of a woman who does not spend any time talking on the phone is 98 pounds.The y-intercept has no practical meaning for this study.The average woman's weight is predicted to be 98.If a woman does not spend any time talking on the phone, then that woman will weigh 98 pounds.

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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	87	48	37	67	42	39	79
Pounds	194	152	154	171	149	128	198

r2r2 = (Round to two decimal places)
Interpret r2r2 :
- Given any group of women who all weight the same amount, 86% of all of these women will weigh the predicted amount.
- 86% of all women will have the average weight.
- 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.
- 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%.
The equation of the linear regression line is:
ˆyy^ = + xx (Please show your answers to two decimal places)
Use the model to predict the weight of a woman who spends 32 minutes on the phone.
Weight = (Please round your answer to the nearest whole number.)
Interpret the slope of the regression line in the context of the question:
- For every additional minute women spend on the phone, they tend to weigh on averge 1.15 additional pounds.
- The slope has no practical meaning since you cannot predict a women's weight.
- As x goes up, y goes up.
Interpret the y-intercept in the context of the question:
- The best prediction for the weight of a woman who does not spend any time talking on the phone is 98 pounds.
- The y-intercept has no practical meaning for this study.
- The average woman's weight is predicted to be 98.
- If a woman does not spend any time talking on the phone, then that woman will weigh 98 pounds.