Modeling linear regression in Excel is easier with the Data Analysis ToolPak. Regression output can be interpreted for both the size and strength of a correlation among one or more variables on the ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

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, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...

We investigate the extension of the nonparametric regression technique of local polynomial fitting with a kernel weight to generalized linear models and quasi-likelihood contexts. In the ordinary ...

As wind energy penetration continues to grow, there is a critical need for probabilistic forecasts of wind resources. In addition, there are many other societally relevant uses for forecasts of wind ...