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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!

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!