1 Getting started

This chapter tells you how to install the necessary software on your computer.

1.1 Installing R

To begin, you will need to install R. This is the engine that runs the code. You need to install the newest version (v4) as well as an older version (v3.6.2).

The older version will be used when running the code from the modules of SOA, which needs to be consistent with what will be installed on the Prometric computers. This course uses the newest version so that you will not have as many errors during practice.

Download it from here: https://cran.r-project.org/mirrors.html

You can easily switch between both of them after installation.

Remember:

For this course, use a version later than 4.0.2.

For the module of SOA, use version 3.6.2.

1.2 Installing RStudio

Just as MS Word creates documents, RStudio creates R scripts and other documents. This is the tool that helps you to write the code. Download the free edition of RStudio Desktop and instal it at your selected location.

Download it from here: https://rstudio.com/products/rstudio/download/

Next you need to set the R library. R code is organized into libraries. You want to use the same code that will be on the Prometric Computers. It would require installing older versions of libraries. Change your R library to the one which was included within the Modules of SOA.

.libPaths("PATH_TO_SOAS_LIBRARY/PAlibrary")

1.3 Download the data

For your convenience, all data in this book, including data from prior exams and sample solutions, has been put into a library called ExamPAData which is available on CRAN.

install.packages("ExamPAData")
library(ExamPAData)

To get the data dictionary for a data set, use ?dataset_name such as ?customer_phone_calls. For your convenience, you can use these data sets for your practice. They make great candidates for machine learning problems.

Dataset	Description
customer_phone_calls	Data used on June 18, 2020 Exam PA
patient_length_of_stay	Data used on June 16, 2020 Exam PA
patient_num_labs	Data used on June 19, 2020 Exam PA
actuary_salaries	DW Simpson actuarial salary data
june_pa	Auto crash data set from SOA June 2019 PA
customer_value	Customer value data set from December 2019 PA
exam_pa_titanic	Titanic passengers as used in ExamPA.net’s practice exam
apartment_apps	Apartment applications as used in ExamPA.net’s Practice Exam
health_insurance	Health insurance claims as used in ExamPA.net’s Practice Exam
student_success	SOA Student Success PA Sample Project, 2019
readmission	SOA Hospital Readmissions Sample Exam, 2019
auto_claim	Automotive claims
boston	Boston housing data set
bank_loans	Credit data from UCI Machine Learning Repository

1.4 Download ISLR

This book references the publically-available textbook “An Introduction to Statistical Learning,” which can be downloaded for free

http://faculty.marshall.usc.edu/gareth-james/ISL/

If you already have R and RStudio installed then skip to “Download the data.”