**How Bad is Multicollinearity?** - Sep 17, 2019.

For some people anything below 60% is acceptable and for certain others, even a correlation of 30% to 40% is considered too high because it one variable may just end up exaggerating the performance of the model or completely messing up parameter estimates.

Tags: Analytics, Multicollinearity, Regression, Statistics

**You have created your first Linear Regression Model. Have you validated the assumptions?** - Nov 15, 2017.

Linear Regression is an excellent starting point for Machine Learning, but it is a common mistake to focus just on the p-values and R-Squared values while determining validity of model. Here we examine the underlying assumptions of a Linear Regression, which need to be validated before applying the model.

Tags: Data Science, Linear Regression, Machine Learning, Multicollinearity, Statistics

**Pros and Pitfalls of Observational Research** - May 3, 2017.

Why the connection between beer brand and region? Climate? Tradition? Or simply distribution? Some combination of the three, plus other factors?

Tags: Correlation, Market Research, Multicollinearity, Research

**A Brief Primer on Linear Regression – Part 2** - Jun 13, 2016.

This second part of an introduction to linear regression moves past the topics covered in the first to discuss linearity, normality, outliers, and other topics of interest.

**Pages:** 1 2

Tags: CleverTap, Multicollinearity, Prediction, Regression