Liz Karns is an epidemiologist and lawyer. Her research interests involve worker health and safety, ethical responsibilities in the conduct of data analysis, and the economic consequences of sexual assault and harassment. Her practice has ranged from individual juvenile clients to large multinational corporations. She is interested in fostering an intellectual environment for students that integrates science, law, and societal needs.
Making statistical predictions based on real-world data is complex and requires a more rigorous statistical model. In this course, you will learn to apply multivariate regression statistical models to make predictions. First, you will identify the variables that best explain your results and define the relationships between dependent and independent variables. You will then practice identifying and interpreting the results of a multiple regression model and making predictions based on that model.
It is recommended to only take this course if you have completed Interpreting and Communicating Data, Using Statistical Test to Make Decisions, and Applying Statistical Tests or have equivalent experience.
- Interpret the variable of interest and its statistical significance while adjusting for potential confounders
- Choose the best model based on relative strength and significance
- Expand the model to improve the fit using multiple regression
How It Works
Who Should Enroll
- Professionals in any industry who need to communicate and interpret data
- Business managers utilizing analytics or benchmarking and comparison
- Professionals from any business function
- Government workers engaged in policy analysis
- Healthcare professionals