Brief Course Description
1. Course Title:
Statistics for Risk Modeling 2
2. Language of Instruction:
Tiếng Việt
3. Course Code:
STA508080
4. Credits:
3
5. Course Objectives:
Provide key concepts of statistical learning and some important algorithms: Principal Component Analysis (PCA), Decision Tree models, and Cluster Analysis. Equip students with the knowledge to define terms used to classify the types of modeling problems and methods; compare the common methods of assessing model accuracy and reliability. Develop data analysis skills related to risk; students will learn to apply these methods in risk modeling. Prepare students for the SRM (Statistics for Risk Modeling) exam by the Society of Actuaries (SOA), USA.
6. Brief Description of Course Content:
This course provides methods and models for risk-related data analysis on the basis of Statistical Learning: Principle Compenent Analysis (PCA), Decision Tree model, Cluster Analysis. The module also includes methods for testing, comparing and choosing between models. This module is developed according to a part of the content of the SRM exam (Statistics for Risk Modeling) of SOA (Society of Actuaries, USA)