# Questions tagged [causality]

The relationship between cause and effect.

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### How exactly does one “control for other variables”?

Here is the article that motivated this question: Does impatience make us fat? I liked this article, and it nicely demonstrates the concept of “controlling for other variables” (IQ, career, income, ...
8answers
39k 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 ...
17answers
62k views

### Under what conditions does correlation imply causation?

We all know the mantra "correlation does not imply causation" which is drummed into all first year statistics students. There are some nice examples here to illustrate the idea. But sometimes ...
7answers
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 ...
6answers
12k views

### Does no correlation imply no causality?

I know that correlation does not imply causality but does an absence of correlation imply absence of causality?
5answers
6k views

### Criticism of Pearl's theory of causality

In the year 2000, Judea Pearl published Causality. What controversies surround this work? What are its major criticisms?
7answers
6k views

### Interview question: If correlation doesn't imply causation, how do you detect causation?

I got this question: If correlation doesn't imply causation, how do you detect causation? in an interview. My answer was: You do some form of A/B testing. The interviewer kept prodding me for ...
3answers
6k views

### Statistics and causal inference?

In his 1984 paper "Statistics and Causal Inference", Paul Holland raised one of the most fundamental questions in statistics: What can a statistical model say about causation? This led to his ...
5answers
31k views

### How are propensity scores different from adding covariates in a regression, and when are they preferred to the latter?

I admit I'm relatively new to propensity scores and causal analysis. One thing that's not obvious to me as a newcomer is how the "balancing" using propensity scores is mathematically different from ...
5answers
108k views

### What do “endogeneity” and “exogeneity” mean substantively?

I understand that the basic definition of endogeneity is that $$X'\epsilon=0$$ is not satisfied, but what does this mean in a real world sense? I read the Wikipedia article, with the supply and ...
10answers
40k views

### What is the difference between prediction and inference?

I'm reading through "An Introduction to Statistical Learning" . In chapter 2, they discuss the reason for estimating a function $f$. 2.1.1 Why Estimate $f$? There are two main reasons we ...
9answers
7k views

### Correlation does not imply causation; but what about when one of the variables is time?

I know this question has been asked a billion times, so, after looking online, I am fully convinced that correlation between 2 variables does not imply causation. In one of my stats lectures today, we ...
3answers
5k views

### Does statistical independence mean lack of causation?

Two random variables A and B are statistically independent. That means that in the DAG of the process: $(A {\perp\!\!\!\perp} B)$ and of course $P(A|B)=P(A)$. But does that also mean that there's no ...
7answers
4k views

### Can cross validation be used for causal inference?

In all contexts I am familiar with cross-validation it is solely used with the goal of increasing predictive accuracy. Can the logic of cross validation be extended in estimating the unbiased ...
2answers
3k views

### How do DAGs help to reduce bias in causal inference?

I have read in several places that the use of DAGs can help to reduce bias due to Confounding Differential Selection Mediation Conditioning on a collider I also see the term “backdoor path” a lot. ...
3answers
9k views

### What's the relation between hierarchical models, neural networks, graphical models, bayesian networks?

They all seem to represent random variables by the nodes and (in)dependence via the (possibly directed) edges. I'm esp interested in a bayesian's point-of-view.
4answers
48k views

### X and Y are not correlated, but X is significant predictor of Y in multiple regression. What does it mean?

X and Y are not correlated (-.01); however, when I place X in a multiple regression predicting Y, alongside three (A, B, C) other (related) variables, X and two other variables (A, B) are significant ...
6answers
5k views

### If 'correlation doesn't imply causation', then if I find a statistically significant correlation, how can I prove the causality?

I understand that correlation is not causation. Suppose we get high correlation between two variables. How do you check if this correlation is actually because of causation? Or,under what conditions, ...
6answers
2k views