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 9 women are shown in the table below. Time 50 28 27 43 55 37 53 58 73 Pounds 127 120 | 109 118 143 126 121 128 153 a. Find the correlation coefficient: r = 0.83 Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: P V = 0 H: P V The p-value is: 0.0056 (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 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 there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. d. r? - 0.68 (Round to two decimal places) e. Interpret r2: O Given any group of women who all weight the same amount, 68% of all of these women will weigh the predicted amount. O There is a 68% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. O 68% of all women will have the average weight. 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 68%. f. The equation of the linear regression line is: ŷ = 92.40 + 0.74 a (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 54 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 0.74 additional pounds. O The slope has no practical meaning since you cannot predict a women's weight. O As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: O The average woman's weight is predicted to be 92. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 92 pounds. 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 92 pounds.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 23PFA
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sub-part 3. please help me with the rest. thanks

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 9 women are shown in the table below.
27 43
109 118
58 73
143 126 121 128 | 153
Time
50
28
55
37
53
Pounds
127 120
a. Find the correlation coefficient: r = 0.83
Round to 2 decimal places.
b. The null and alternative hypotheses for correlation are:
Ho: p V = 0
H1: p V + 0
The p-value is: 0.0056
(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 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 there is a correlation between the
time women spend on the phone and their weight. Thus, the regression line is useful.
d. r2 = 0.68
|(Round to two decimal places)
e. Interpret r2 :
O Given any group of women who all weight the same amount, 68% of all of these women will
weigh the predicted amount.
O There is a 68% chance that the regression line will be a good predictor for women's weight
based on their time spent on the phone.
O 68% of all women will have the average weight.
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 68%.
f. The equation of the linear regression line is:
ý = 92.40
+ 0.74
* (Please show your answers to two decimal places)
g. Use the model to predict the weight of a woman who spends 54 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 0.74
additional pounds.
O The slope has no practical meaning since you cannot predict a women's weight.
O As x goes up, y goes up.
i. Interpret the y-intercept in the context of the question:
O The average woman's weight is predicted to be 92.
O The best prediction for the weight of a woman who does not spend any time talking on the
phone is 92 pounds.
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 92
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 9 women are shown in the table below. 27 43 109 118 58 73 143 126 121 128 | 153 Time 50 28 55 37 53 Pounds 127 120 a. Find the correlation coefficient: r = 0.83 Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: p V = 0 H1: p V + 0 The p-value is: 0.0056 (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 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 there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. d. r2 = 0.68 |(Round to two decimal places) e. Interpret r2 : O Given any group of women who all weight the same amount, 68% of all of these women will weigh the predicted amount. O There is a 68% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. O 68% of all women will have the average weight. 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 68%. f. The equation of the linear regression line is: ý = 92.40 + 0.74 * (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 54 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 0.74 additional pounds. O The slope has no practical meaning since you cannot predict a women's weight. O As x goes up, y goes up. i. Interpret the y-intercept in the context of the question: O The average woman's weight is predicted to be 92. O The best prediction for the weight of a woman who does not spend any time talking on the phone is 92 pounds. 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 92 pounds.
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