Capture relationships between data sets by graphing linear equations in Microsoft Excel 2007. Linear equations allow you to predict values within your data set and view the overall trend.

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

I use Python 3 and Jupyter Notebooks to generate plots and equations with linear regression on Kaggle data. I checked the correlations and built a basic machine learning model with this dataset.

Learn how to build a multivariate linear regression model step by step—no libraries, just pure C++ logic!

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 ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.

To accommodate the potential non-linear covariate effect, we consider a non-parametric regression model for panel count data. The regression B-splines method is used to estimate the regression ...

Homoskedastic refers to a condition in which the variance of the error term in a regression model is constant. Learn more about its importance and how it is used.

Residual plots can be used to validate assumptions about the regression model.