Statistics for Data Science and Business Analysis - A2. No Endogeneity

The video tutorial discusses omitted variable bias in regression analysis, explaining how it occurs when a relevant variable is not included in the model, leading to biased and counterintuitive results. An example involving real estate pricing in London illustrates the issue, showing how the omission of a location variable skewed results. The tutorial emphasizes the importance of including all relevant variables to avoid bias and suggests strategies for identifying and correcting omitted variable bias.

What steps can be taken to ensure that relevant variables are included in a regression model?

How can one identify and address omitted variable bias in their analysis?