Confounding Variables
Confounding variables are variables that affect the dependent variable and are related to the independent variable, making it difficult to determine the true relationship between the two. In data science and artificial intelligence, confounding variables can lead to biased or inaccurate results in predictive models. It is important to identify and control for confounding variables in order to accurately measure the effect of the independent variable on the dependent variable. This can be done through techniques such as stratification, matching, and regression analysis.
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