In a regression and correlation analysis, if r² = 1, then

A) SSE must also be equal to one.
B) SSE must be equal to zero.
C) SSE can be any positive value.
D) SSE must be negative.

Question

In a regression and correlation analysis, if r 2  = 1, thenA)  SSE must also be equal to one.B)  SSE must be equal to zero.C)  SSE can be any positive value.D)  SSE must be negative.

Heidi Windsor · Accepted Answer

Final Answer : B, Explanation :  The correlation coefficient (r) measures the strength and direction of the relationship between two variables. A perfect positive correlation between two variables is denoted by r = 1. In this case, r 2  = 1 indicates a perfect positive linear relationship between the variables  2 and  .In a regression analysis, the sum of squared errors (SSE) measures the variability that is not explained by the regression equation. If r = 1, then the regression equation perfectly explains the relationship between the variables, and there is no variability left unexplained. This means that SSE must be equal to zero, as all the data points fall on the regression line.Therefore, the best choice is B: SSE must be equal to zero.

In a regression and correlation analysis, if r² = 1, then

A) SSE must also be equal to one.
B) SSE must be equal to zero.
C) SSE can be any positive value.
D) SSE must be negative.

Definitions

Learning Objectives

Learning Objectives

Related questions

In a regression and correlation analysis, if r2 = 1, thenA) SSE must also be equal to one.B) SSE must be equal to zero.C) SSE can be any positive value.D) SSE must be negative.

Definitions

Learning Objectives

Learning Objectives

Related questions

In a regression and correlation analysis, if r² = 1, then

A) SSE must also be equal to one.
B) SSE must be equal to zero.
C) SSE can be any positive value.
D) SSE must be negative.