What is the relationship between the number of minutes er day a woman spends talking on the phone and the roman's weight? The time on the phone and weight for 7 romen are shown in the table below. Time Pounds 41 32 131 112 144 a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: 20 The p-value is: places) 90 32 31 33 82 104 113 120 142 ² c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. (Round to four decimal 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. 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. d. e. Interpret ²: 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) O There is a 81% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. O81% of all women will have the average weight. O Given any group of women who all weight the same amount, 81% of all of these women will weigh the predicted amount. 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 81%. 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 41 minutes on the phone. Weight= (Please round your answer to the nearest whole number.)
What is the relationship between the number of minutes er day a woman spends talking on the phone and the roman's weight? The time on the phone and weight for 7 romen are shown in the table below. Time Pounds 41 32 131 112 144 a. Find the correlation coefficient: r = Round to 2 decimal places. b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: 20 The p-value is: places) 90 32 31 33 82 104 113 120 142 ² c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. (Round to four decimal 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. 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. d. e. Interpret ²: 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) O There is a 81% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. O81% of all women will have the average weight. O Given any group of women who all weight the same amount, 81% of all of these women will weigh the predicted amount. 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 81%. 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 41 minutes on the phone. Weight= (Please round your answer to the nearest whole number.)
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
![/hat is the relationship between the number of minutes
er day a woman spends talking on the phone and the
roman's weight? The time on the phone and weight for 7
romen are shown in the table below.
Time
Pounds
41 32
131 112
a. Find the correlation coefficient: r =
Round to 2 decimal places.
b. The null and alternative hypotheses for correlation
are:
Ho: ? = 0
H₁: ? # 0
The p-value is:
places)
90 32 31 33 82
144 104 113 120 142
c. Use a level of significance of a = 0.05 to state the
conclusion of the hypothesis test in the context of
the study.
(Round to four decimal
● 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.
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 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. ²
e. Interpret 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)
O There is a 81% chance that the regression line
will be a good predictor for women's weight
based on their time spent on the phone.
O 81% of all women will have the average
weight.
O Given any group of women who all weight the
same amount, 81% of all of these women will
weigh the predicted amount.
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
81%.
f. The equation of the linear regression line is:
ý =
answers to two decimal places)
(Please show your
g. Use the model to predict the weight of a woman who
spends 41 minutes on the phone.
Weight=
the nearest whole number.)
(Please round your answer to](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7ff36ea4-4b9a-42ce-ad1e-51a4d88fb5fb%2F32f76daf-9ddc-4493-86e7-9666a2c460a4%2Ffiqbnl_processed.jpeg&w=3840&q=75)
Transcribed Image Text:/hat is the relationship between the number of minutes
er day a woman spends talking on the phone and the
roman's weight? The time on the phone and weight for 7
romen are shown in the table below.
Time
Pounds
41 32
131 112
a. Find the correlation coefficient: r =
Round to 2 decimal places.
b. The null and alternative hypotheses for correlation
are:
Ho: ? = 0
H₁: ? # 0
The p-value is:
places)
90 32 31 33 82
144 104 113 120 142
c. Use a level of significance of a = 0.05 to state the
conclusion of the hypothesis test in the context of
the study.
(Round to four decimal
● 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.
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 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. ²
e. Interpret 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)
O There is a 81% chance that the regression line
will be a good predictor for women's weight
based on their time spent on the phone.
O 81% of all women will have the average
weight.
O Given any group of women who all weight the
same amount, 81% of all of these women will
weigh the predicted amount.
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
81%.
f. The equation of the linear regression line is:
ý =
answers to two decimal places)
(Please show your
g. Use the model to predict the weight of a woman who
spends 41 minutes on the phone.
Weight=
the nearest whole number.)
(Please round your answer to
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