M. Elizabeth Karns is a lawyer and epidemiologist. Her teaching is directly connected to her practice, which has focused on statistical evidence, occupational illnesses, assault and harassment injuries, and reproductive harms. Professor Karns has been involved in every aspect of the data life cycle, from initial design to post-event forensic evaluations. Her work on data science ethics brings together professional practice norms, individual values, and organizational goals. Professor Karns is currently developing a virtual reality experience based on the unintended consequences of automated fraud detection.
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.
You are required to have completed the following courses or have equivalent experience before taking this course:
- Interpreting and Communicating Data
- Using Statistical Test to Make Decisions
- Applying Statistical Tests
Key Course Takeaways
- 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
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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