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Consider the following regression output: = 0.2033 + 0.656Xt se = (0.0976) (0.1961) r² = 0.397 RSS = 0.0544 ESS = 0.0358 Where: Y = labor force participation rate (LFPR) of women in 1972 and X = LFPR of women in 1968. The regression results were obtained from a sample of 19 cities in the United States.

Consider the following regression output: = 0.2033 + 0.656Xt se = (0.0976) (0.1961) r² = 0.397 RSS = 0.0544 ESS = 0.0358 Where: Y = labor force participation rate (LFPR) of women in 1972 and X = LFPR of women in 1968. The regression results were obtained from a sample of 19 cities in the United States.

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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How do you interpret this regression?
Consider the following regression output: Ŷt = 0.2033 +0.656Xt se (0.0976) (0.1961) r² = 0.397 RSS=0.0544 ESS = 0.0358 Where: Y = labor force participation rate (LFPR) of women in 1972 and X = LFPR of women in 1968. The regression results were obtained from a sample of 19 cities in the United States.
Transcribed Image Text:Consider the following regression output: Ŷt = 0.2033 +0.656Xt se (0.0976) (0.1961) r² = 0.397 RSS=0.0544 ESS = 0.0358 Where: Y = labor force participation rate (LFPR) of women in 1972 and X = LFPR of women in 1968. The regression results were obtained from a sample of 19 cities in the United States.
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