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.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
need help please!
![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.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdfbe6a76-33fb-4739-b913-a49b2ab2e0d7%2F0f7b6a73-ffa6-48a7-87fe-1587c3bdecae%2Frywzlsg_processed.jpeg&w=3840&q=75)
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.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdfbe6a76-33fb-4739-b913-a49b2ab2e0d7%2F0f7b6a73-ffa6-48a7-87fe-1587c3bdecae%2Fs7cr07h_processed.jpeg&w=3840&q=75)
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.
Expert Solution
![](/static/compass_v2/shared-icons/check-mark.png)
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 3 steps with 10 images
![Blurred answer](/static/compass_v2/solution-images/blurred-answer.jpg)
Recommended textbooks for you
![MATLAB: An Introduction with Applications](https://www.bartleby.com/isbn_cover_images/9781119256830/9781119256830_smallCoverImage.gif)
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
![Probability and Statistics for Engineering and th…](https://www.bartleby.com/isbn_cover_images/9781305251809/9781305251809_smallCoverImage.gif)
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
![Statistics for The Behavioral Sciences (MindTap C…](https://www.bartleby.com/isbn_cover_images/9781305504912/9781305504912_smallCoverImage.gif)
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
![MATLAB: An Introduction with Applications](https://www.bartleby.com/isbn_cover_images/9781119256830/9781119256830_smallCoverImage.gif)
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
![Probability and Statistics for Engineering and th…](https://www.bartleby.com/isbn_cover_images/9781305251809/9781305251809_smallCoverImage.gif)
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
![Statistics for The Behavioral Sciences (MindTap C…](https://www.bartleby.com/isbn_cover_images/9781305504912/9781305504912_smallCoverImage.gif)
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
![Elementary Statistics: Picturing the World (7th E…](https://www.bartleby.com/isbn_cover_images/9780134683416/9780134683416_smallCoverImage.gif)
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
![The Basic Practice of Statistics](https://www.bartleby.com/isbn_cover_images/9781319042578/9781319042578_smallCoverImage.gif)
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
![Introduction to the Practice of Statistics](https://www.bartleby.com/isbn_cover_images/9781319013387/9781319013387_smallCoverImage.gif)
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman