(e) Find the value of the coefficient of determination r2. what percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for 2 to four decimal plac Round your answers for the percentages to two decimal place.) explained unexplained (f) Considering the values of r and r2, does it make sense to use the least-squares line for prediction? Explain your answer. O The correlation between the variables is so low that it makes sense to use the least-squares line for prediction. O The correlation between the variables is so high that it makes sense to use the least-squares line for prediction. O The correlation between the variables is so high that it does not make sense to use the least-squares line for prediction. O The correlation between the variables is so low that it does not make sense to use the least-squares line for prediction.
(e) Find the value of the coefficient of determination r2. what percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for 2 to four decimal plac Round your answers for the percentages to two decimal place.) explained unexplained (f) Considering the values of r and r2, does it make sense to use the least-squares line for prediction? Explain your answer. O The correlation between the variables is so low that it makes sense to use the least-squares line for prediction. O The correlation between the variables is so high that it makes sense to use the least-squares line for prediction. O The correlation between the variables is so high that it does not make sense to use the least-squares line for prediction. O The correlation between the variables is so low that it does not make sense to use the least-squares line for prediction.
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
Does prison really deter violent crime? Let x represent percent change in the rate of violent crime and y represent percent change in the rate of imprisonment in the general U.S. population. For 7 recent years, the following data have been obtained.
I need help with (d) (e) and (f)

Transcribed Image Text:Does prison really deter violent crime? Let x represent percent change in the rate of violent crime and y represent percent change in the rate of imprisonment in the general U.S. population. For 7 recent years, the following data have been obtained.
6.0
5.9
4.2
5.2
6.2
6.5
11.1
y
-1.5
-4.0
-7.4
-4.0
3.6
-0.1
-4.4
Complete parts (a) through (e), given Ex = 45.1, Ey = -17.8, Ex? = 319.39, Ey? = 121.34, Exy = -111.65, and rx 0.0648.
(b) Verify the given sums Ex, Ey, Ex?, Ey2, Exy, and the value of the sample correlation coefficient r. (Round your value for r to four decimal places.)
Σχ
Ey =|
Ex2 =
Ey2 =
Σχy
r =
(c) Find x, and y. Then find the equation of the least-squares line ŷ = a + bx. (Round your answer to four decimal places.)
x =
y =
ŷ =
(d) Graph the least-squares line. Be sure to plot the point (x, y) as a point on the line.
y
y
10
10
5
5
a
b.
-5
2
4.
6
8
10
12
14
4
8
10
12
14
y
y
10
10H
5
5
of
C
d.
X
2
4
8
10
12
14
2
4
8
10
12
14

Transcribed Image Text:(e) Find the value of the coefficient of determination r2. What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line? What percentage is unexplained? (Round your answer for r2 to four decimal places.
Round your answers for the percentages to two decimal place.)
r2 =
explained
%
unexplained
%
(f) Considering the values of r and r2, does it make sense to use the least-squares line for prediction? Explain your answer.
O The correlation between the variables is so low that it makes sense to use the least-squares line for prediction.
O The correlation between the variables is so high that it makes sense to use the least-squares line for prediction.
O The correlation between the variables is so high that it does not make sense to use the least-squares line for prediction.
O The correlation between the variables is so low that it does not make sense to use the least-squares line for prediction.
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