Linear regression is a statistical method used to understand the relationship between an outcome variable and one or more explanatory variables. It works by fitting a regression line through the ...

Simple linear regression is commonly used in forecasting and financial analysis—for a company to tell how a change in the GDP could affect sales, for example. Microsoft Excel and other software ...

Wrapping Up The k-NN regression system presented in this article is the simplest possible version. In the early days of machine learning, several variations of k-NN regression were explored, for ...

In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

Linear ridge regression (LRR) is a relatively simple variation of standard linear regression. However, LRR and standard linear regression are usually considered distinct techniques, in part because ...

In particular, we propose a criterion for choosing the response variable in a simple linear regression problem. An example from the domain of finance illustrates our purpose. We find evidence under ...

Sample size planning is one of the most important issues in the design of a study. Simple and accurate sample size formulas for a desired confidence interval width have been developed for many ...

Linear Regression vs. Multiple Regression Example Consider an analyst who wishes to establish a relationship between the daily change in a company's stock prices and daily changes in trading volume.

In our example of simple linear regression 1, we saw how one continuous variable (weight) could be predicted on the basis of another continuous variable (height). To illustrate classification ...