Course: Regression Models

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Regression Models



Brian Caffo, Roger Peng, and Jeff Leek



Offered By:

Department of Biostatistics


Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist's toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing.

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This course is available as part of the Johns Hopkins Data Science Specialization on Coursera.