Regression Modeling in Practice

This course is part of Data Analysis and Interpretation Specialization

Instructors: Jen Rose +1 more

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Skills you'll gain

  •   SAS (Software)
  •   Predictive Modeling
  •   Statistical Programming
  •   Regression Analysis
  •   Scatter Plots
  •   Plot (Graphics)
  •   Correlation Analysis
  •   Statistical Hypothesis Testing
  •   Data Analysis
  •   Statistical Analysis
  •   Statistical Modeling
  • There are 4 modules in this course

    This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you.

    Basics of Linear Regression

    Multiple Regression

    Logistic Regression

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