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 Pounds 98 141 119 = 0 65 33 144 101 = 34 56 109 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? H₁: ?0 The p-value is: 32 140 116 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 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. 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) 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 71%. 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. O 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.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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#
d. 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)
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%.
O Given any group of women who all weight the same amount, 71% of all of these women will
weigh the predicted amount.
O71% of all women will have the average weight.
O 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 =
80
F3
+
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.
(Please show your answers to two decimal places)
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.
Olf a woman does not spend any time talking on the phone, then that woman will weigh 93
pounds.
000
000
F4
do
%
F5
<
MacBook Air
F6
&
F7
*
DII
F8
DD
F9
Transcribed Image Text:# d. 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) 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%. O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O71% of all women will have the average weight. O 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 = 80 F3 + 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. (Please show your answers to two decimal places) 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. Olf a woman does not spend any time talking on the phone, then that woman will weigh 93 pounds. 000 000 F4 do % F5 < MacBook Air F6 & F7 * DII F8 DD F9
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 =
b. The null and alternative hypotheses for correlation are:
Ho: ?
0
H₁: ?0
The p-value is:
80
F3
(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.
34 56
109 140
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.
$
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.
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. ²2 =
(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%.
200
F4
32
116
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.
O 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.
%
Round to 2 decimal places.
F5
A
F6
MacBook Air
&
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 = b. The null and alternative hypotheses for correlation are: Ho: ? 0 H₁: ?0 The p-value is: 80 F3 (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. 34 56 109 140 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. $ 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. 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. ²2 = (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%. 200 F4 32 116 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. O 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. % Round to 2 decimal places. F5 A F6 MacBook Air & F7 - * DII F8 F9
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