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.
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- 5 stars61.90%
- 4 stars25.27%
- 3 stars6.22%
- 2 stars3.66%
- 1 star2.93%
REGRESSION MODELING IN PRACTICE의 최상위 리뷰
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.
Great course. The instructors could have gone a bit slow during the session on multiple regression.
Great explanation of stat and useful coding examples.
I enjoy this course so far. I like how the course entirely depends on peer grading. It will help us to get some honest feedback on our research.
Data Analysis and Interpretation 특화 과정 정보
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