Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

where Y is the response, or dependent, variable, the Xs represent the p explanatory variables, and the bs are the regression coefficients. For example, suppose that you would like to model a person's ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...

Regression is a statistical tool used to understand and quantify the relation between two or more variables. Regressions range from simple models to highly complex equations. The two primary uses for ...

Successful investing requires the ability to distinguish long-term trends from the short-term noise that moves stock prices on a minute-to-minute basis. One way to tune out the random oscillations and ...

Goodness-of-fit statistics for general multiple-linear-regression equations are reviewed for the case of replicated responses. A modification of the coefficient of determination is recommended. This ...