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Quantifying Relationships with Regression Models
Coursera MOOC / Non-credit 0

Quantifying Relationships with Regression Models

About this course

This course will introduce you to the linear regression model, which is a powerful tool that researchers can use to measure the relationship between multiple variables. We’ll begin by exploring the components of a bivariate regression model, which estimates the relationship between an independent and dependent variable. Building on this foundation, we’ll then discuss how to create and interpret a multivariate model, binary dependent variable model and interactive model. We’ll also consider how different types of variables, such as categorical and dummy variables, can be appropriately incorporated into a model. Overall, we’ll discuss some of the many different ways a regression model can be used for both descriptive and causal inference, as well as the limitations of this analytical tool. By the end of the course, you should be able to interpret and critically evaluate a multivariate regression analysis.

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90/100

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39/45
Who stands behind it
35/35
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16/20

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What you'll learn

  • interpret a multivariate regression analysis
  • create and interpret a bivariate regression model
  • incorporate categorical and dummy variables into regression models
  • evaluate the limitations of regression analysis

Course objectives

  • introduce linear regression modeling
  • explore the use of regression for causal inference
  • analyze different types of variables in regression modeling
Data Analysis #data interpretation #regression analysis #statistical modeling #data analysis #causal inference #linear regression #dummy variables #multivariate modeling #bivariate modeling #categorical variables
$49.00

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