38k views

### Does causation imply correlation?

Correlation does not imply causation, as there could be many explanations for the correlation. But does causation imply correlation? Intuitively, I would think that the presence of causation means ...
18k views

### The Book of Why by Judea Pearl: Why is he bashing statistics?

I am reading The Book of Why by Judea Pearl, and it is getting under my skin1. Specifically, it appears to me that he is unconditionally bashing "classical" statistics by putting up a straw man ...
3k views

### Introduction to causal analysis

What are good books that introduce causal analysis? I'm thinking of an introduction that both explains the principles of causal analysis and shows how different statistical methods could be used to ...
2k views

### Hiding a Regression Model from Professor (Regression Battleship) [closed]

I'm working on a homework assignment where my professor would like us to create a true regression model, simulate a sample of data and he's going to attempt to find our true regression model using ...
3k views

### Which Theories of Causality Should I know?

Which theoretical approaches to causality should I know as an applied statistician/econometrician? I know the (a very little bit) Neyman–Rubin causal model (and Roy, Haavelmo etc.) Pearl's Work on ...
7k views

### What's the difference between “mean independent” and independent?

As stated in the Econometrics textbook (Introductory Econometrics by Wooldbridge): When $E(u|x)=E(u)$ holds, we say that $u$ is mean independent of $x$. Why can't we simply say that $u$ is ...
968 views

### Correlation, regression and causal modeling

This is probably a blindingly obvious answer for any seasoned statistician, but I am still confused as to how correlation differs from regression, technically. I understand that one is a measure of ...
968 views

### OLS Population Orthogonality Condition Proof

In the OLS model, we assume that $E(X'U)=0$ (with $u$ being the error term), which comes from $E(U|X=x)=0$, providing us that $E(U)=0$ and $cov(x_i, u)=0$ $\forall x_i$. I understand this argument ...
Greene [1] and Wooldridge [2] emphasize that in the standard multiple linear regression model $${\bf y}=X{\bf b}+{\bf e}$$ a key assumption is that $$E[{\bf e}|X]=E[{\bf e}].$$ Or, in other words, $X$...