There are several different methods of making forecasts, but they all fall into two categories: causal methods and time-series methods. Linear regression forecasting is a time-series method that ...

Interestingly, time can still be modelled by our linear model easily and the fitted linear model can be further used to make time series predictions. In Exercise 2 and 3, we will learn how to analyse ...

The goal of a time series regression problem is best explained by a concrete example. Suppose you own an airline company and you want to predict the number of passengers you'll have next month based ...

xkcd #2048 is exceptionally relevant to this. Doing linear regression well with a big dataset is difficult! I do this all the time at work and honestly I often show a scatter plot without any ...

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 ...

Nonlinear models are more complicated than linear models to develop because the function is created through a series ... regression can be used is to predict population growth over time.

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, ...