Linear and logistic regression models can be created using R, the open-source statistical computing software. In this course, biotech expert and epidemiologist Monika Wahi uses the publicly available Behavioral Risk Factor Surveillance Survey (BRFSS) dataset to show you how to perform a forward stepwise modeling process. Monika shows you how to design your research by considering scientific plausibility selecting a hypothesis. Then, she takes you through the steps of preparing, developing, and finalizing both a linear regression model and a logistic regression model. She also shares techniques for how to interpret diagnostic plots, improve model fit, compare models, and more.
Topics include:

   Dealing with scientific plausibility
   Selecting a hypothesis
   Interpreting diagnostic plots
   Working with indexes and model metadata
   Working with quartiles and ranking
   Making a working model
   Improving model fit
   Performing linear regression modeling
   Performing logistic regression modeling
   Performing forward stepwise regression
   Estimating parameters
   Interpreting an odds ratio
   Adding odds ratios to models
   Comparing nested models
   Presenting and interpreting the final model