Question

Adding all variables to a regression that increase the R-Squared by any amount, large or small, is likely to result in: A: The best possible regression model. B: Creating a model that is over-specified and hard to interpret. C: Running out of data. D: Including more variables than are necessary.

Name: adding all variables to a regression that increase the r squared by any amount large or small is likely to result in a the best possible regression model b creating a model that is over spec 47295
Uploaded: 2023-08-31T10:42:39-08:00
Duration: 1 min 2 s
Channel: Sri K
Description: adding all variables to a regression that increase the r squared by any amount large or small is likely to result in a the best possible regression model b creating a model that is over spec 47295

          Adding all variables to a regression that increase the R-Squared by any amount, large or small, is likely to result in:
A: The best possible regression model.
B: Creating a model that is over-specified and hard to interpret.
C: Running out of data.
D: Including more variables than are necessary.

Added by Cheryl L.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

Instant Answer

Solved by Expert Sri K

08/31/2023

Step 1

Step 1: Recognize that R-squared measures the proportion of variance explained by the model and can increase simply by adding more predictors, even if they are not truly related to the outcome. Show more…

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Adding all variables to a regression that increase the R-Squared by any amount, large or small, is likely to result in: A: The best possible regression model. B: Creating a model that is over-specified and hard to interpret. C: Running out of data. D: Including more variables than are necessary.