Looking for information about quantitative psychology

[dmacfour]

As of this summer I'll have masters degrees in both applied statistics and experimental psychology, and the idea of bringing those two domains together for a PhD is very appealing. That being said, I don't know much about the field yet and was wondering if anyone here could answer a few questions:

1. What does the profile of a competitive applicant look like?

2. What are some hot areas of research to consider? 

3. What level of mathematical ability is recommended to excel in a quant psych program?

[psychology_student_]

1. What does the profile of a competitive applicant look like?

• Research experience and proof of it (posters, articles)

2. What are some hot areas of research to consider? 

• No one can fricken honestly answer that. Check some .gov sites (NSF, NIMH) and look at what people are getting funded for.

3. What level of mathematical ability is recommended to excel in a quant psych program?

• I'd say to excel in a phd quant psych program you'd need a pretty damn high level of math self-efficacy and math abilities

[dmacfour]

On 3/19/2019 at 11:02 PM, personallycentered said:

 3. What level of mathematical ability is recommended to excel in a quant psych program?

• I'd say to excel in a phd quant psych program you'd need a pretty damn high level of math self-efficacy and math abilities

What do you mean by "pretty damn high"? In my current masters program that means that you're doing a lot of mathematical proofs, but in my previous masters program that meant that you used calculus and linear algebra. I'm wondering if I need to take more proof based classes (like real analysis) to excel in a quant psych program. 

Edited April 1, 2019 by dmacfour

[dancedementia]

7 hours ago, dmacfour said:

What do you mean by "pretty damn high"? In my current masters program that means that you're doing a lot of mathematical proofs, but in my previous masters program that meant that you used calculus and linear algebra. I'm wondering if I need to take more proof based classes (like real analysis) to excel in a quant psych program. 

You'll probably want to take advance calc, linear algebra, differential equations, combinatorics, and loooooots of probability/random variables/stats courses. Topics to get familiar with might include distribution functions (binomial, geometric, poisson, exponential, gamma, beta), conditional probability, Bayes, Chebyshev, LLN, CLT, nonparametric stats, ANOVAs, regressions, decision theory, large sample theory, asymptotic efficiency, sequential analysis.

Some knowledge of programming languages (e.g. C++, Python) might also help.

Edited April 2, 2019 by dancedementia

[psychology_student_]

On 4/1/2019 at 1:09 PM, dmacfour said:

What do you mean by "pretty damn high"? In my current masters program that means that you're doing a lot of mathematical proofs, but in my previous masters program that meant that you used calculus and linear algebra. I'm wondering if I need to take more proof based classes (like real analysis) to excel in a quant psych program. 

idk what i exactly meant by damn high math knowledge just like idk what you mean by "excel". if you think you need to learn more than you just should do it, idk that's what i would do. there's a ton of free stuff online for extra math help. heck even khan academy has stuff on diff eq and stuff on linear algebra if you're having trouble grasping your current class.  #knowledge is power?

[GradPerson]

This might be something you could reach out to programs about to start that line of communication. Explain a bit about your background and ask about what their quant program looks for in applicants.

All the quant programs I looked at also accepted people with BS/MS degrees in math rather than psych, so I'd say you need a large amount of math under your belt. Probably more than just a regular psych degree would give, but I can't be certain. I'm also not sure what all you did in your stats program, but that might help.

[StatsLove]

I figured I would throw in my two cents on this topic.  I was accepted into two quant PhD programs this admissions cycle, so while I can't speak to what would help you excel while in the program just yet, I can offer some answers from the perspective of a recent applicant.  

1. What does the profile of a competitive applicant look like?

I think a competitive quant applicant looks similar to other branches of competitive psychology applicants.  The most important elements of your application are your research fit with your POI and your research background.  Schools want to see that you can do research and get them publications, and that your interests align with their faculty since you'll be working with them for the next few years.   A broad math background is beneficial, but the scope what is necessary depends on the program (more about this for question 3).  Strong GPA, GRE, and LoR are also helpful.

2. What are some hot areas of research to consider? 

I wouldn't focus on what's exactly "hot," but what programs and professors you're interested in are doing.  I've read a good amount of recent papers exploring different ways to use Bayesian models, but my POIs weren't focusing their research on the subject so it wouldn't have been that helpful trying to find training in it.  It wouldn't have hurt to have, but I don't think it would have given me a significant advantage over other applicants.  You should identify what you would enjoy researching (perhaps based off of your previous experience) and look at professors who do similar work.

3. What level of mathematical ability is recommended to excel in a quant psych program?

It depends on the program, but you don't need to have experience with every math subject in the book to be considered.  I'm sure as much math experience as you can get will only help your application, but it's not always necessary.  You're applying to a quant PhD to get that high level training and doing research with it, so it's not expected that you have all that knowledge already going into the program.  For reference, I only have undergraduate statistics and calculus courses under my belt and not a lot of programming experience, but what I have learned/have done research with closely aligns to the research of my future advisor.  Again, though, it definitely depends on the program and the professors you're applying to.

A lot of the programs you will find are designed to be accessible to students who didn't get a master's (like me), so I'd say you have a leg up in some regards since you have that extra math experience.

Hopefully this was helpful for you,  I had a lot of the same questions going into this application cycle.  If you have any other questions feel free to reach out on this threat or DM me.