Course Syllabus

Here is an outline of the course contents. See the supporting pages for more detailed descriptions.

Day 1. Introduction

This day is devoted to an introduction/review of the statistical package R in the context of analyzing loss data. Specifically,

• Introduction to Loss Data Analytics, Chapter 1 of Loss Data Analytics.

• Introduction to R using Datacamp

  • The companion site, Loss Data Analytics with R

• Frequency Models, Chapter 2 of Loss Data Analytics. See also the companion site, Loss Data Analytics with R

• Modeling Loss Severity, Chapter 3 of Loss Data Analytics, as time permits. See also the companion site, Loss Data Analytics with R

Day 2. Loss Data Analytics

This day will cover severity, estimation, and premium chapters (3,4,7) from the open source book Loss Data Analytics.

• Chapters 3, 4, 7 of Loss Data Analytics.

  • See also the companion site, Loss Data Analytics with R

Day 3. Regression Modeling

This day reviews the theory of linear regression and develops the implementation in the context of the software R.

We review the theory as explained in my regression textbook, Regression Modeling with Actuarial and Financial Applications.

• • • An online version is available for the next few months at http://www.ssc.wisc.edu/~jfrees/regression/ the password (needed for Chaps 3 and on) is "@ S R M I" without quotes, without spaces.

For the implementation, we will go through the companion Online Tutorial.

• • The seminar also draws on resources from the series, Predictive Modeling Applications in Actuarial Science.

Day 4. Generalized Linear Models and Survival Models

This day introduces the generalized linear model using Chapters 11, 12, 13 of my regression textbook, Regression Modeling with Actuarial and Financial Applications.

We will also cover Chapter 8 of Loss Data Analytics to show how this is used in an insurance pricing context.

Day 5. Survival Models and Course Wrap-Up

We will cover

• • Survival model Chapter 14 of my regression textbook, Regression Modeling with Actuarial and Financial Applications.

  • Survival Model Chapter 19 from the series, Predictive Modeling Applications in Actuarial Science.

The seminar also draws on resources from the series, Predictive Modeling Applications in Actuarial Science.