Timeline for Why, intuitively, does redundancy in a multiple linear regression increase the standard error of the partial regression coefficients? [duplicate]
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| Apr 21, 2020 at 14:01 | history | duplicates list edited | whuber♦ | duplicates list edited from What is the effect of having correlated predictors in a multiple regression model? to What is the effect of having correlated predictors in a multiple regression model?, Mathematical Basis behind inflation of Standard errors of Regression estimates due to multicollinearity | |
| Apr 21, 2020 at 14:01 | history | closed | whuber♦ | Duplicate of What is the effect of having correlated predictors in a multiple regression model? | |
| Apr 20, 2020 at 20:22 | comment | added | dimitriy | See here and here. | |
| Apr 20, 2020 at 20:07 | comment | added | Henry | Suppose you did an OLS regression against two explanatory variables which were essentially identical except for tiny rounding issues. You could increase the coefficient for one and decrease the coefficient for the other without any noticeable change in the fit for the dependent variable. So you could not rely on the coefficients you actually see to any extent (though their sum might be meaningful) | |
| Apr 20, 2020 at 19:59 | history | asked | AlphaOmega | CC BY-SA 4.0 |