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WebAssign for Devore's Probability and Statistics for Engineering and the Sciences, 9th Edition [Instant Access], Single-Term
9th Edition
ISBN: 9780357893104
Author: Devore; Jay L.
Publisher: Cengage Learning US
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Textbook Question
Chapter 12.2, Problem 23E
a. Obtain SSE for the data in Exercise 19 from the defining formula [SSE = Σ(yi − ŷi)2], and compare to the value calculated from the computational formula.
b. Calculate the value of total sum of squares. Does the simple linear regression model appear to do an effective job of explaining variation in emission rate? Justify your assertion.
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Students have asked these similar questions
1. (30 pts) We wish to determine a regression equation that relates the length of an infant (in cm) to age (in days), gender and
weight at birth (in kg). Below is portion of the regression analysis derived using a software. *Note: under the gender
variable: male and female categories are assigned a value of 1 and 0, respectively.
Std. Err.
0.0980
Source
Coef.
Model
Residual
316.8866
age
weight
gender
intercept
0.4798
0.4020
1.3113
71.4734
8
1.0454
1.9591
19.53
7.7829
a. What is the sample size for this problem?
b. Write the estimated regression equation, interpret each slope coefficients, use the proper unit of measurement.
c. Test for significance of the Bage, Bweight, and Bgender at the 99% confidence level.
d. From (b) which parameter/s is/are statistically significant.
e. Test whether or not there is a significant relationship between the infant's length and the independent variables. Use a
.01 level of significance. Use only the critical value approach.
f. Provide the Coefficient…
A linear regression model has been estimated for the variables Y="monthly consumption of veal (kg)", X1="monthly monetary household income (thousand EUR)" and X2="household size (number of members)" using data for a random sample of 80 households. The following results have been obtained:
b0=0.3 b1=0.5 b2=0.7 R-sq=0.9 R=0.95，Interpret the value of regression coefficient b2.
13) Use computer software to find the multiple regression equation. Can the equation be used for
prediction? An anti-smoking group used data in the table to relate the carbon monoxide( CO)
of various brands of cigarettes to their tar and nicotine (NIC) content.
13).
CO TAR
NIC
15
1.2
16
15
1.2
16
17
1.0
16
6.
0.8
1
0.1
1
8.
0.8
8.
10
0.8
10
17
1.0
16
15
1.2
15
11
0.7
9.
18
1.4
18
16
1.0
15
10
0.8
9.
0.5
18
1.1
16
A) CO = 1.37 + 5.50TAR – 1.38NIC; Yes, because the P-value is high.
B) CÓ = 1.37 - 5.53TAR + 1.33NIC; Yes, because the R2 is high.
C) CO = 1.25 + 1.55TAR – 5.79NIC; Yes, because the P-value is too low.
D) CO = 1.3 + 5.5TAR - 1.3NIC; Yes, because the adjusted R2 is high.
%3D
Chapter 12 Solutions
WebAssign for Devore's Probability and Statistics for Engineering and the Sciences, 9th Edition [Instant Access], Single-Term
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