- Recall bias
- Selection bias
- Collider bias
- Omitted variable bias

Types of Bias

http://approximatelycorrect.com/2016/11/07/the-foundations-of-algorithmic-bias/http://approximatelycorrect.com/2016/11/07/the-foundations-of-algorithmic-bias/

The Foundations of Algorithmic Bias



This article talks about how algorithms make decisions, how does machine learning relate to it, and it dissects many foundation ways algorithm and ML can go wrong and cause biases. It is a good indepth article on this topic.

algorithm and bias

A point estimator is a function that returns an estimate denoted by $\hat\theta$, using a given set of data as an input 

Point Estimators

Bias is a systematic error in the estimate of an association between cause and effect. It may result from poor diagnosis/diagnostic criteria, poor case choice, poor choice of controls or variation in the way risk exposure is measured in case and controls.

University of Michigan - Ann Arbor

Georgetown University

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, pp. 3-7). New York: springer.

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