![You’ve run the regression. You see the t’s, the β’s, and the p’s. But what do they mean? Don’t panic. This book will tell you.
[T]he estimators in common use almost always have a simple interpretation that is not heavily model dependent…. A leading example is linear regression, which provides useful information about the conditional mean function regardless of the shape of this function. Likewise, instrumental variables estimate an average causal effect for a well-defined population even if the instrument does not affect everyone.
Hooray!](http://25.media.tumblr.com/tumblr_l582noaIGD1qc38e9o1_250.png)
You’ve run the regression. You see the t’s, the β’s, and the p’s. But what do they mean? Don’t panic. This book will tell you.
[T]he estimators in common use almost always have a simple interpretation that is not heavily model dependent…. A leading example is linear regression, which provides useful information about the conditional mean function regardless of the shape of this function. Likewise, instrumental variables estimate an average causal effect for a well-defined population even if the instrument does not affect everyone.
Hooray!
