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, ...

Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension ... Categorical data analysis, including contingency table ...

Here, we look at how to use data imported into Microsoft Excel to perform a linear regression and how to interpret the results. Linear regression models the ... required to chart a linear ...

x ijp]' The Generalized Estimating Equation of Liang and Zeger (1986) for estimating the p ×1 vector of regression parameters is an extension ... matrix that is often used in generalized linear models ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as to ...

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.

The mean response is modeled as a logistic regression model using the explanatory ... Initial parameter estimates for iterative fitting of the GEE model are computed as in an ordinary generalized ...