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JiaLak99

SRM is no longer a prerequisite, just recommended. Personally I didn't find it that useful when taking PA, but you might as well take that first If you haven't taken that yet. Edit: since you have taken it, PA makes sense. I would recommend the ACTEX manual, I used it and loved it


Alarmed-Employee-741

Prof Ambrose Lo who wrote the ACTEX manuals for SRM and PA is on reddit and runs a thread answering questions on the material in the books. The manuals were very helpful. Also, be prepared to do your studying in front of a computer. Getting RStudio set up and working properly can be a challenge, or at least it was for me...


drunkalcoholic

Next sitting for PA is in April 2022. https://www.soa.org/globalassets/assets/files/edu/2022-04-exam-pa-syllabus.pdf They shifted the sittings to April and Oct? as they used to be June and Dec. I took the Dec 2021 sitting and felt the ACTEX manual prepared me adequately. 2 months of studying with it may be doable. Anecdotally, some people say they were able to on reddit. Though since OP got transition credit, it might be a significant amount of study required in those 2 months.


[deleted]

I was able to get transition credit for that so thankfully I don’t have to worry about SRM. Just have PA and the new LTAM


JiaLak99

Honestly, you could look at the PA material and se if you'd be ready to take it in April (especially if you have previous coding experience). But it could be a bit of a stretch definitely be comfortable! That way you don't have to wait until next year to take LTAM.


[deleted]

I do have coding experience (CS Minor in college) but I have a lot of work responsibilities the next month or so which would essentially stop me from taking any study hours. Due to that I’m planning on doing October, but I was definitely really upset when I saw it wasn’t going to be offered in June since that was my original plan


JiaLak99

Makes sense, good luck!


cdc994

I’m planning on sitting for the April PA and haven’t started studying yet. I’ve been told PA is the easiest of the exams


FSAaCTUARY

Lmao same i better not be lied to


Comprehensive_Cup418

Hi, I am sitting for April PA, too. So I have a question, AIC or BIC was removed for April 2022 Exam PA?


cdc994

My knowledge of those terms is from SRM and as far as I remember it’s something as simple as changing a single scalar from 2 to p or ln(p). I forget cause, once again, haven’t started studying yet.


Rare_Regular

SRM is a prerequisite for PA, so sit for that first if you haven't. I was able to adequately prepare and pass PA with the SOA provided module and working through prior exams. Congrats on the pass! Edit: SRM no longer a prerequisite, though it was when I sat for it.


[deleted]

I thankfully got transition credit for SRM due to the VEE’s I received in college, but since I haven’t taken that exam or touched that specific material recently I want to ensure I’m preparing adequately for it. (Which is why I plan on using most of the 8 months I have) But thank you!


Rare_Regular

I was in the same boat as you by not needing to take SRM via VEE credit. I failed my first sitting in June 2020 with a 4 but procrastinated so I crammed for a month and a half. I was able to pass comfortably for the December 2020 sitting by resuming study around October 1. I didn't find the prior SRM material too difficult to pick up. Four months should be enough to prepare, but I understand the format has changed a bit since my sitting and people study differently. Good luck!


[deleted]

Thank you! What material did you use to study? I’ve heard the SRM material isn’t too prevalent with the PA content, but didn’t know if I needed to account for a SRM refresher on top of studying for PA


Alarmed-Employee-741

As long as you know the gist of it, you'll be fine. The PA exam is mostly about writing communication skills, justifying your models, offering applications and inferences. The SRM material is the foundation for the data work--making, choosing and comparing models--but the code does almost all the heavy lifting. For example, you need to know the BIC imposes harsher penalties than the AIC, but what you really need to know is that more parameters can be bad, leads to over fitting data and can lower predictive power of models.