Ementorhub

What you'll learn

Use regression analysis, least squares and inference

Understand ANOVA and ANCOVA model cases

Investigate analysis of residuals and variability

Describe novel uses of regression models such as scatterplot smoothing

Skills you'll gain

Predictive Modeling

Statistical Analysis

Data Science

Statistical Inference

Probability & Statistics

Regression Analysis

Statistical Modeling

There are 4 modules in this course

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.

Week 2: Linear Regression & Multivariable Regression

Week 3: Multivariable Regression, Residuals, & Diagnostics

Week 4: Logistic Regression and Poisson Regression