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3. Statements about regression Aa Aa Which of the following are true about regression with one predictor variable (often called "simple regression")? Check all that apply. The regression equation is the line that best fits a set of data as determined by having the least squared error. The slope describes the amount of change in Y for a one-unit increase in X. After conducting a hypothesis test to test that the slope of the regression equation is nonzero, you can conclude that your predictor variable, X, causes Y. A

3. Statements about regression Aa Aa Which of the following are true about regression with one predictor variable (often called "simple regression")? Check all that apply. The regression equation is the line that best fits a set of data as determined by having the least squared error. The slope describes the amount of change in Y for a one-unit increase in X. After conducting a hypothesis test to test that the slope of the regression equation is nonzero, you can conclude that your predictor variable, X, causes Y. A

MATLAB: An Introduction with Applications
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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3. Statements about regression Aa Aa Which of the following are true about regression with one predictor variable (often called "simple regression")? Check all that apply. The regression equation is the line that best fits a set of data as determined by having the least squared error. The slope describes the amount of change in Y for a one-unit increase in X. After conducting a hypothesis test to test that the slope of the regression equation is nonzero, you can conclude that your predictor variable, X, causes Y.
Transcribed Image Text:3. Statements about regression Aa Aa Which of the following are true about regression with one predictor variable (often called "simple regression")? Check all that apply. The regression equation is the line that best fits a set of data as determined by having the least squared error. The slope describes the amount of change in Y for a one-unit increase in X. After conducting a hypothesis test to test that the slope of the regression equation is nonzero, you can conclude that your predictor variable, X, causes Y.
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