Every released Exam PA sitting is free on FreeFellow as a graded walkthrough: October 2023, April 2024, October 2024, April 2025 and October 2025. The just-released April 2026 exam is up too, and its published model solution goes in as soon as it's available. There are also 500 free concept-check questions and 22 free lessons. I'm Jeffrey Ting, an FSA and CFA, and I built FreeFellow so good exam prep could be free.

What Exam PA is, and why practice looks different

Exam PA (Predictive Analytics) isn't multiple choice. It's a 3.5-hour open-response exam: you're handed a business data problem and type written responses to specific tasks in Microsoft Word, with Microsoft Excel also available, and you're graded on the quality and correctness of what you write. It's an Associate-level (ASA) exam, and most candidates take it after SRM.

Since the April 2023 administration, R and RStudio aren't available during the exam. All the relevant R code and output are in the exam materials, and your job is to read and interpret that output, not write or run code under time pressure. The skills that matter are reading model output, reasoning about it, and writing clear, complete answers to what each task asks.

So PA prep can't look like prep for the multiple-choice exams. There's no giant answer bank that mirrors it. What transfers is writing responses to real released tasks and then grading yourself strictly against the rubric.

What's free for PA

Samples are open without signup, and the full free content needs a free account, with no credit card.

Each released administration is reproduced verbatim from the SOA's published Project Statements and Model Solutions. For every task you write your own answer first, then compare it with the model solution, the graders' comments and a point-by-point rubric. You'll find them at the PA walkthroughs.

Because each walkthrough comes from a real released sitting, it maps to the exam almost one to one. The Project Statement is the business problem candidates faced, the tasks are the same tasks, the model solution is the graded answer, and the graders' comments tell you what they valued and penalized. I've split each sitting into its tasks so you can write one at a time, and turned the model solution and comments into a rubric you can score against.

The 500 concept-check questions are short items across the syllabus for drilling the underlying ideas quickly. They're separate from the written exam; use them to confirm you understand a concept before you try to write about it under exam conditions.

The 22 lessons, plus a formula and technique sheet and a glossary, give you the conceptual backbone: what each method does, when to use it, how to read its output and how to talk about it precisely. It's all under the free Exam PA practice page.

How to practice the writing

This is the part candidates skip, and it's what decides your score. Reading a model solution and nodding along won't get you there, so write your own answer cold first.

Here's the loop I recommend:

  1. Open a task from a released sitting. Read the Project Statement context and the specific ask.
  2. Type your full written response, the way you would in Word on exam day, without peeking at the solution. If the task points to R output, work from that output as you would in the real exam.
  3. Only then reveal the model solution, the graders' comments and the rubric.
  4. Score yourself point by point. Where you lost marks, you usually knew the method but didn't say what the rubric wanted, stated a result without the required justification, or skipped a step the graders explicitly rewarded.
  5. Rewrite the weak parts until your answer would earn the points.

For grading, free users get a copy-to-AI prompt for each task, so you can paste your answer and the rubric into your own ChatGPT or Claude and get a structured critique. Fellow includes five AI-graded attempts a day inside the platform, against the same rubric. Either way, the standard comes from the published model solution and graders' comments, not from my opinion.

Across all the released sittings you'll start to recognize the recurring task types: describe a variable and its issues, justify a modeling choice, interpret a coefficient or a tree split, compare models, recommend and defend. The exam reuses these shapes even as the data changes.

A realistic plan is to get through the concept checks and a few lessons first so the methods are solid, then spend most of your time writing task responses from the released sittings, oldest to newest. Save one full recent sitting to do timed near the end, so you get a feel for the 3.5-hour pacing.

FreeFellow is independent of the Society of Actuaries. The materials I reproduce are the published Project Statements and Model Solutions, and I'd encourage you to read the source documents directly as well.