A survey is conducted on 700 Californians older than 30 years of age. The study wants to obtaininference on the relationship between years of education and yearly income in dollars. The responsevariable is income in dollars and the explanatory variable is years of education.A simple linear regression model is fit, and the output from R is below:Im(formula = Income ~ Education, data = CA)Coefficients:Estimate Std. Error t value Pr(>|t|)(Intercept) 25200.25 1488.94 16.93 3.08e-10 ***Education 2905.35 112.61 25.80 1.49e-12 ***Residual standard error: 32400 on 698 degrees of freedomMultiple R-squared: 0.7602 The p-value to test if Education is a significant predictor (previous question) is approximately 0.Make a conclusion at a 5% significant level.We conclude evidence that Education is a significant predictor.We conclude we do not evidence that Education is a significant predictor.

From the given information, the p-value to test if Education is a significant predicator is about 0.

The p-value to test if Education is a significant predictor (previous question) is approximately 0 Make a conclusion at a 5% significant level. O We conclude evidence that Education is a significant predictor. O We conclude we do not evidence that Education is a significant predictor.

The p-value to test if Education is a significant predictor (previous question) is approximately 0 Make a conclusion at a 5% significant level. O We conclude evidence that Education is a significant predictor. O We conclude we do not evidence that Education is a significant predictor.

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

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...

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Question

A survey is conducted on 700 Californians older than 30 years of age. The study wants to obtain
inference on the relationship between years of education and yearly income in dollars. The response
variable is income in dollars and the explanatory variable is years of education.
A simple linear regression model is fit, and the output from R is below:
Im(formula = Income ~ Education, data = CA)
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25200.25 1488.94 16.93 3.08e-10 ***
Education 2905.35 112.61 25.80 1.49e-12 ***
Residual standard error: 32400 on 698 degrees of freedom
Multiple R-squared: 0.7602

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