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 ...

Python allows free creation of plots, unlike expensive, stagnant graphing calculators. Import NumPy and Matplotlib for basic linear and polynomial plots in Python. Seaborn lets you make ...

A linear regression is a statistical model that attempts to show the relationship between two variables with a linear equation. A regression analysis involves graphing a line over a set of data ...

Figure 2: In a linear regression relationship, the response variable has a distribution for each value of the independent variable. (a) At each height, weight is distributed normally with s.d. σ = 3.

Often, regression models that appear nonlinear upon first glance are actually linear. The curve estimation procedure can be used to identify the nature of the functional relationships at play in ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

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 ...

A class of estimates for regression parameters in a linear model with right censored data is proposed. These estimates are derived by using linear rank tests for right censored data as estimating ...