Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

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 ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The growth of the stock market, for example, might be predicted using multiple linear regression. Logistic regression.

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems.

Linear regression analyzes two separate variables in order to define a single relationship. In chart analysis, this refers to the variables of price and time.

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