Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

Perhaps the most fundamental type of R analysis is linear regression. Linear regression can be used for two closely related, but slightly different purposes. You can use linear regression to predict ...

Regression models for competing risks data analysis The most commonly used regression model for analyzing event-time data is the Cox proportional hazards model.

Lesson 9 Simple Linear Regression The purpose of this tutorial is to continue our exploration of multivariate statistics by conducting a simple (one explanatory variable) linear regression analysis.

DTSA 5011 Modern Regression Analysis in R DTSA 5011 Modern Regression Analysis in R Specialization: Statistical Modeling for Data Science Applications Instructor: Brian Zaharatos, Director, ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

R-squared is a statistical measure that indicates how much of the variation of a dependent variable is explained by an independent variable in a regression model. In investing, R-squared is ...

Logistic regression with binary and multinomial outcomes is commonly used, and researchers have long searched for an interpretable measure of the strength of a particular logistic model. This article ...

The paper is prompted by certain apparent deficiences both in the discussion of the regression model in instructional sources for geographers and in the actual empirical application of the model by ...