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.
- 5 stars61.76%
- 4 stars25.36%
- 3 stars6.25%
- 2 stars3.67%
- 1 star2.94%
REGRESSION MODELING IN PRACTICE からの人気レビュー
Great course. The instructors could have gone a bit slow during the session on multiple regression.
This was a great course. I've done a few in the area of stats, regression and machine learning now and the Wesleyan ones are the most well-rounded of all of them
I really like this training. It's good if you want a good view of applied regression.
This is a great beginner level course for those have no programming experience. But I would suggest the content to be extended to 8 weeks instead of 4 weeks.
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