A scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. The p-value of the ANOVA F test will be very large, since it's clear that all of the variables are good predictors of salary very small, since it's clear that all of the variables are good predictors of salary very large, since it's clear that none of the variables are good predictors of salary very small, since it's clear that none of the variables are good predictors of salary
A scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. The p-value of the ANOVA F test will be very large, since it's clear that all of the variables are good predictors of salary very small, since it's clear that all of the variables are good predictors of salary very large, since it's clear that none of the variables are good predictors of salary very small, since it's clear that none of the variables are good predictors of salary
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
A scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. The p-value of the ANOVA F test will be
very large, since it's clear that all of the variables are good predictors of salary
very small, since it's clear that all of the variables are good predictors of salary
very large, since it's clear that none of the variables are good predictors of salary
very small, since it's clear that none of the variables are good predictors of salary
Transcribed Image Text:Predictor
Coef
SE Coef
P
Constant
17.846931
2.001876
8.915
0.0001
Years
1.103130
0.359573
3.068
0.0032
Papers
0.321520
0.037109
0.0002
Sex
1.593400
0.687724
2.317
0.0083
Grants
1.288941
0.298479
4.318
0.0003
S= 1.75276
R-sq = 92.3%
adj R-sq = 91.4%
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