Use your knowledge about ANOVA tables and adjusted R-squared values to answer this question: As the sample size goes up, the average amount of variability explained (non-adjusted R-squared value) by a random (zero true predictive power) explanatory variable in regression: Group of answer choices goes down stays the same goes up

Use your knowledge about ANOVA tables and adjusted R-squared values to answer this question: As the sample size goes up, the average amount of variability explained (non-adjusted R-squared value) by a random (zero true predictive power) explanatory variable in regression: Group of answer choices goes down stays the same goes up

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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Consider the following ANOVA table for a multiple regression model relating housing prices (in thousands of dollars) to the number of bedrooms in the house and the size of the lot on which the house was built (in square feet). There were 9090 total observations. Estimated Price=20,160.07+2188.83(Bedrooms)+0.2139(Lot Size)Estimated Price=20,160.07+2188.83(Bedrooms)+0.2139(Lot Size) ANOVA dfdf SSSS MSMS F� Significance F� Regression 22 306,443.7975306,443.7975 153,221.8988153,221.8988 21.727421.7274 2.2211E-082.2211E-08 Residual 8787 613,525.5190613,525.5190 7052.01757052.0175 Total 8989 919,969.3165919,969.3165 What percent of variation in housing prices is explained by the number of bedrooms and lot size? Round your answer to two decimal places
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