Multiple Linear Regression Analysis
Description
Multiple linear regression is a statistical technique used to analyze the relationship between multiple independent variables (predictors) and a single dependent variable (outcome). Unlike simple linear regression, which involves only one independent variable, multiple linear regression considers two or more predictors. It is widely used in various fields, including economics, finance, social sciences, and more, to understand and predict the behavior of dependent variables based on multiple influencing factors.
Purpose
This is applicable when the data are multivariate. A multiple linear regression model relates a response variable Y to more than one explanatory variable. The main purpose of the multiple regression analysis is to find which explanatory variables contribute to the variation of the response variable. We are usually looking for the ‘best’ subset of the explanatory variables.
$195 (Fee covers training materials)
July 4 and 6 2026 10:00 am - 12:00 pm MT
Expected Learning Outcomes
By the end of this training, you will be able to
explain the assumptions underlying multiple linear regression; and
demonstrate the applications of multiple linear regression.
Target Learners
This training program is designed for individuals or groups of people who work in clinical settings, academia, pharmaceutical industries, Government, corporations, nonprofit organizations, and organizations that work on biological data.
Learning Approach
Programs are delivered through live online interactive sessions with seasoned instructors having vast experiences in academia. Contents are well structured and manageable with self-paced learning activities and exercises. Our approach provides learners opportunities for hands-on practice, asking questions, investigating problems, and applying their knowledge to solve complex scenarios or real-world problems. In the end, learners develop deeper understanding, critical thinking, and problem-solving skills.
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