| ## About | |
| The R library for [PredictiveInsightsAI.com](PredictiveInsightsAI.com), **the comprehensive, all-in-one solution to help you pass PA**. Includes practice exams and quizzes and video tutorials. Don’t let PA stop you from earning your ASA! | |
| 5 years. That’s the average time required to pass all the exams to get an ASA. | |
| The pass rate of PA is only 50%. And this includes people who are taking PA for a second time. | |
| Having to retake PA adds another 6 months to this journey. | |
| ## 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. | |
| ```{r eval = F} | |
| 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 own 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 PredictiveInsightsAI.com's practice exam | | |
| |`apartment_apps`| Apartment applications as used in PredictiveInsightsAI.com's Practice Exam| | |
| |`health_insurance`| Health insurance claims as used in PredictiveInsightsAI.com'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 | | |