wolmoth

So relaying more info on what I wrote above, after having talked to more professors, they said this year they received almost twice as many applicants as usual, where the average is around 20. So only 40 applicants for an extreme year seems more mild than what could be expected as something on the low end for clinical psych.

I don't really know anything about clinical programs, but I will just say what I know about quant. 1) It is hard to gage this for quant as the application statistics for quant programs are either non-existent or often aggregated into some general "other" group (with other fields like health psyche) where the study doesn't supply the non-aggregated stats for these other psych fields. At least, this has been my experience. From what professors at these programs have told me, they say they get less applicants than other fields, but it doesn't mean they are necessarily easy to get into. I've had, in my interviews, people tell me they were interviewing about 10 other applicants. This year, however, is probably an outlier for an accurate representation of how it usually goes. A "difficulty" in Quant compared to other psyche fields would probably be the need for mathematical competence. Some programs expect more from your background than others, so you would need to know how you stack up on that regard and what your realistic options are. 2) Every program has offered me full tuition plus a stipend. Most have said they provide guaranteed funding for certain things like travel and conferences though some have said you need to apply. Again, this year has made it a bit harder for the programs in this regard, hence why most schools cannot admit the amount of students they usually would. I would say, I am guessing your funding is probably less reliant on research grants, at least initially, because it is often not even expected that you have a in-depth knowledge/skills of stats/math/coding to conduct research. So the schools are usually more generous earlier on. A lot of this is anecdotal based on the few programs I appleid, and I am sure other people have better info than I do. In general, quant produces good money for departments and it is cheap (no lab upkeep other than software licenses), so they will most likely have funding. 3) I think it is helpful to demonstrate any background knowledge in these subjects as the opportunity to learn them in undergrad (which I assume you are) is less frequent. If you can demonstrate a more in-depth understanding of your PI's research, that will stick out because many applicants do not have this level of comprehension (nor is in-depth comprehension expected most of the time). It is common that most grad students have to take a while learning the topics before committing to research topics, so if you have some knowledge of what you can pursue past the point of vague ideas, this would probably stick out.

Has anyone heard back from UC Davis yet? They are the only one left for me, but idk if its just me who hasn't heard back yet.

I asked the interviewer about the interview process, and he said this would be the only one they will do unless they have difficulty deciding and need to bring a couple of candidates in one more time to help them make the final cut. So unless that happens that will be the only time we have to meet face-to-face. He only asked like one question about me/my experience. Idk if that is good or bad. The rest I was just asking about the program. If you have more questions I would definitely email them as there was a lot even I couldn't ask that I wanted to.

I'd probably try to get a job with some commercial lab that does animal testing (there are some in the area) mainly because I have a lot of experience with rat research. Other than that, I'd probably try to get certified in SAS or something and try to code somewhere, which would probably be harder as my experience is more limited.

Didn't apply there so I can't tell you. Perhaps they are being pickier due to budget cuts. Some programs told me they only had enough resources to let in, at most, two students. Perhaps, UNC wanted to play very picky this year and is only looking at like 5 people at most. But this is just speculation. In other topic... did anyone else who did the Fordham interviews think it was really really short? Just 30 minutes for the only interview (unless the race is too close to call and they need another)? They hardly asked me anything it felt like. I assume they have there reasons to keep it short, but I feel it would be difficult for the admissions team to make a decision from this.

Just out of curiosity, how did you get the opportunities to learn these while in undergrad? Were they topics you just self-taught? That is the best I could do with Bayesian stats as my school doesn't offer undergraduate courses for either of those two, which seems to be the common case. I had an informal interview with the PIs I wrote about in my SoP. My focus of interest was on longitudinal design and missing data analysis, however. So the PIs I met with were probably not the ones you want to work with. So, at least for me, I am probably not much of a direct competition. It is a bit unfortunate as student budgets are a bit more stretched this year due to the pandemic circumstances. I would not worry though. Looking back at previous years notices when they got interviews, most schools, like UCLA, don't say much until mid January.

Quick piece of advice for your interviews because this just happened to me. Make sure you know how to explain concepts such as a p-value or the central limit theorem. Luckily, I rehearse those two definitions a lot on my own so I never come off as a fraud if I don't get them perfect lol, but I did not prepare for those type of potential questions. I could see this easily trip some people up if they don't have those definitions ingrained in their heart, and it seems like the type of question meant to see if you actually understand basic concepts. Just a forewarning to those who might need it.

I've heard back from Notre Dame and USC for interviews. POIs from both (who've I have been in personal contact with previously, which I suspect is at least why they got back to me so soon) both reach out to me individually. The Notre Dame one wants to set up a Zoom interview next week, which is way sooner than I have prepared for tbh (I haven't prepared for interviews at all yet lol). Also, the USC message didn't outright say I had an interview but to "lookout" for the first week of February when they are doing them. So it was heavily implied. I still haven't heard back from three schools (UC Davis, UCLA, and Fordham) though and don't expect to until next month! It is still very early. Usually you don't even hear back until January. I got the Notre Dame message today and the USC one about a week after I applied (one of my LoR also was a previous student for the USC prof, so I also assume that's part of why they got back so quickly). Do not fret if you haven't heard yet! I am sure many schools are still trying to figure out how they are going to do everything during the pandemic anyway. I'm applying PhD btw, because that might matter for how fast they get back to people but idk on that aspect.

My school has a quant program, and here's what a professor told me about the GRE scores (since they are still requiring it). The purpose of GRE is mainly to get a sense of your aptitude for quantitative reasoning and your skillset in that regard. This is the main way they tell for most applications, so hence why the program at my school is still requiring them. If you do not have anything to demonstrate your capability with quantitative skills, I would recommend taking and submitting the GRE. If you have a large list of, say, math/stats classes with high GPA or some proof that you have done quant based work in the past, then needing the GRE as proof is probably not as important. Obviously, if you do it and did really well on it, it's not going to hurt you any way. I decided to opt out of the GRE because most of the schools I wanted to apply to weren't requiring it, and I felt my background was substantial proof enough that I am capable of doing quant-related research. Of course, there was one school that was on my list that was still requiring it, but oh well. 2020 existential dread hit me hard in the the summer, and my motivation to study for the test was completely killed to the point where if I did take the test, I probably wouldn't have done well. Also, I am busy af this semester and did not know how I would fit time to study and take practice tests. I'm confident that my decision won't hurt me, and I might as well take advantage of the unique opportunity given here. But you need to assess your skill set and if it demonstrates your capability well enough. How many math and stats courses have you taken and how well have you done on them? Do you have any research experience regarding statistical modeling in your past that can demonstrate you know what you're getting into and have the ability to follow through? These are important questions for these programs regardless, but the GRE is an important way these programs discard those that's aren't qualified while also giving credit to those who are qualified but just didn't have the chance to take those classes or do prior research. Everyone comes from a different background, and the GRE quant section gives many people the opportunity to demonstrate capability on-par with those who have more of a history with quant. These programs want to give people a chance, hence why they aren't down right refusing test scores. Some programs are still requiring it though because they weight the skillset demonstrated form this more heavily.

From what I've been told, it depends the program you apply to. Some are much more technical and other's less so. If you are trying to apply to ASU or Notre Dame, for example, you definitely need a good background in math/stats. I can't speak for programs that aren't as demanding for those skills because those aren't the ones I have been looking at. You do need a good basis in coding regardless. I've been teaching myself some R basics like how to build Monte Carlos, for example. So having a background in CS is definitely not a bad thing as it demonstrates competency with code. That being said, you are expected to have some background in math/stats, so you can't go into it with little to none.

Oh I can think of some methods I want to learn more about, but I have no clue on any research questions. "Broadly" I can ask something along the lines of "how can this method be further developed and/or applied more broadly." I know you can look at the latest research and see what gaps they mention, but again, I need a bit more background. I guess I have a few months before I need to come up with something more definitive for a statement of purpose.

How the heck are you guys going about narrowing down potential advisors? Some of the stuff that they research, I've had no relevant coursework, and you can only learn so much from their papers without any basis on the subject. I've spent so much time learning stuff like Bayesian models just so I can understand what they are doing. I feel this has limited me the most in deciding on any school.