In a simple linear regression model, B1 has important relationships with a sample correlation coefficient r. Prove the following two identities.

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
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ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
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Chapter3: Straight Lines And Linear Functions
Section3.4: Linear Regression
Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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In a simple linear regression model, B1 has important relationships with a sample
correlation coefficient r. Prove the following two identities.
Tyn – 2
Syy
SIT
(2)
se(3)
(1) B
Transcribed Image Text:In a simple linear regression model, B1 has important relationships with a sample correlation coefficient r. Prove the following two identities. Tyn – 2 Syy SIT (2) se(3) (1) B
Expert Solution
Step 1

1.

Consider, the regression equation is,

Y=β0+β1X+ε

By minimizing the least squares equation,

β^1=X-X¯Y-Y¯X-X¯2

Formula for correlation between X and Y is,

r=X-X¯Y-Y¯X-X¯2Y-Y¯2

Variance of X and variance of Y are,

Sxx=X-X¯2Syy=Y-Y¯2

Consider,

rSyySxx=X-X¯Y-Y¯X-X¯2Y-Y¯2*Y-Y¯2X-X¯2              =X-X¯Y-Y¯X-X¯2Y-Y¯2*Y-Y¯2X-X¯2             =X-X¯Y-Y¯X-X¯2            =β^1

Thus, rSyySxx=β^1.

 

 

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