Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

Logistic regression is preferrable over a simpler statistical test such as chi-squared test or Fisher’s exact test as it can incorporate more than one explanatory variable and deals with possible ...

The primary goal of a linear regression training algorithm is to compute coefficients that make the difference between reality and the model’s predictions consistently small.

Regression can be used on categorical responses to estimate probabilities and to classify.

Course TopicsIn this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as:1) How to use the F-test to determine ...

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...

Linear regression captures the relationship between two variables—for example, the relationship between the daily change in a company's stock prices and the daily change in trading volume.