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.

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

How to Do Residuals in Excel. Linear regression models predict the outcome of one variable based on the value of another, correlated variable. Excel 2013 can compare this data to determine the ...

Multiple regression models with survey data Regression becomes a more useful tool when researchers want to look at multiple factors simultaneously. If we want to know whether the racial divide ...

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, ...

Linear forecasting models can be used in both types of forecasting methods. In the case of causal methods, the causal model may consist of a linear regression with several explanatory variables.

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 43, No. 3 (September/septembre 2015), pp. 358-377 (20 pages) Diagnostics for heteroscedasticity in linear regression ...

However, for some generalized linear regression models, the distribution of deviance residuals may be very far from normality, and therefore the corresponding normal Q-Q plots may be misleading to ...