f. The equation of the linear regression line is: (Please show your answers to two decimal places)

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.3: Modeling Data With Power Functions
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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 = 0.84
b. The null and alternative hypotheses for correlation are:
Ho: P = 0
H₁: p0
The p-value is: 0.00861 (Round to four decimal places)
80
F3
>
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.
34
109
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.
d. ² = 0.71
(Round to two decimal places)
-59
There is statistically significant evidence conclude that there is a correlation between the
time women spend on the phone and their weight. Thus, the regression line is useful.
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%.
f. The equation of the linear regression line is:
$
F4
56
32
140 116
O Given any group of women who all weight the same amount, 71% of all of these women will
weigh the predicted amount.
O 71% of all women will have the average weight.
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.
do
Round to 2 decimal places.
%
F5
(Please show your answers to two decimal places)
F6
&
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 = 0.84 b. The null and alternative hypotheses for correlation are: Ho: P = 0 H₁: p0 The p-value is: 0.00861 (Round to four decimal places) 80 F3 > 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. 34 109 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. d. ² = 0.71 (Round to two decimal places) -59 There is statistically significant evidence conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. 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%. f. The equation of the linear regression line is: $ F4 56 32 140 116 O Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. O 71% of all women will have the average weight. 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. do Round to 2 decimal places. % F5 (Please show your answers to two decimal places) F6 & F7 DII F8 F9
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