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Dec 26, 2024
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AC 3414 - Linear Models and Predictive Analytics4 lecture hours 0 lab hours 4 credits
Course Description
This course is designed for actuarial science majors to provide them a solid statistical foundation. This course will cover topics that are not included in MA 2410 and MA 2411 . It will introduce the theory and practical application of linear models and predictive analytics techniques, which are commonly used for insurance modeling work. (prereq: MA 2410 and MA 2631 and (MA 232 or MA 2323 ))
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Employ fundamental exploratory data analysis on data
- Use appropriate linear models such as generalized linear models and generalized additive models for analyzing the data.
- Understand the key concepts of dimension reduction using principal components analysis
- Apply predictive analytics techniques on real-life problems
- Use R or other statistical software to solve a problem in topics covered in this course
- Interpret results for various linear models and predictive analytics
Prerequisites by Topic
- Calculus (single variable and multivariable)
- Probability theory and application
- Statistics
Course Topics
- Explanatory data analysis
- Generalized linear model
- Generalized additive models
- Principle component analysis
- Penalized regression
- Decision tree and cluster analysis
Coordinator
Dr. Won Chul Song
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