Left Skew

Anyone know the Penn State results poster POI?

I've yet to hear back from any I/O programs, beyond UMD (SDOS) where I was wait-listed. Don't lose faith. Not saying I'm a good baseline but at least you're not alone.

My goal during this process is not to receive a rejection. I don't need to be accepted anywhere, I just don't want to be rejected. I want act like I just gave them the wrong email. Penn state must've got the emailed someone else...

Hello all, I'm back again with some more data. For those of you that are unfamiliar with my original post, I create a procedure in R that scrapes the results survey and output some pretty-ish graphics from the data. After a bit of cleaning and consolidating, I looked into things like: common interview days, most popular schools, and most popular program types... The data is based on self-report and isn't always the cleanest, so I have't taken the initiative to make more profound "predictions". But here I am, one last time, to give some info on the qualitative metrics behind an application (i.e., GPA, GRE Verbal, GRE Quant, GRE AWA) to see if there is really a difference in those that get accepted and those that get rejected. I split the data further by program type; however, some of the programs (e.g., Developmental Psych, Quant Psych, Neuro) had such a small sample of candidate that reported their scores that I had to aggregate them-- these programs are in "psychology: other". Once again this data is not parametric because it lacks independence of scores and possibly normalcy. A candidate may be in the rejected or accepted sample multiple times given they reported their scores for multiple schools, so be cautious when coming to conclusions. Also we have no clue how accurate reported scores are; candidates may have forgotten their score or flipped their quant and verbal (these are things I cannot account for). Conclusion: I had to actually go back and look at the raw data because the results weren't as I expected. There are many occasions where those rejected had a higher average than those accepted. I will work on further validating my numbers but I can say that the average score between those rejected and those accepted (based on the Grad Cafe sample) don't seem to consistently differ. This trend is not consistent across programs. Social Psych applicants seem like the smarties among the top program-types. Another conclusion is that it seems the grad cafe sample is higher on these metrics than an average applicant (I need to do more research) but given the average GRE scores are definitely above the 50th percentile, GPA is also high too. The data is on the last few pages. Those of you that haven't seen the other graphics please feel free. You can see it HERE. I'm also going to attach the file for those of you that don't trust clicking links (though I promise it's safe). Grad Cafe Decisions.pdf

Isn't all of SPU based on faith? For those of you that applied, did that aspect influence you more than anything? They'd definitely reject me.

I've had two so far (this year), a few more during my masters, and a lot of job interviews will try my best to give you some tips. A majority of the time you will sense the formality. Most faculty will present an overview of the program, process, etc. You'll pick up on how they present themselves. If you don't get a good estimate I like to lead with: "How do you like to be addressed?" My personal goal is to be unique. I tend to pick at least one question that isn't the traditional "what is the funding like", "how is research", "how strong is the advisor structure"....yet not nebulous. Some examples: 1. How do you support students emotionally and socially? 2. If I did something wrong, like ran the wrong analysis or read the wrong article, how would you react? 3. Looking back, is there anything you wish you knew in graduate school? 4. If you selected students based on just one metric (i.e., GRE, GPA, Recommendations, Interview, Personal Statement, CV, experience...), what would you choose and why? Best,

By my comment I meant "started sending results" not "completed results", sorry for the confusion. I've scraped the results survey with R and attached some longitudinal data for I/O decisions. See the title of each page for the type of decision. I've attached it. As you can tell the sample size isn't so strong...so take it for what it's worth. Takeaways: Jan 15th - Feb 15th seems like peak time for interviews February is ride or die: 23rd - 28th prime for interviews but rejection is also high in Feb Notice that the Accepted numbers are higher than the others, this may be due to self-selection but let's hope that it isn't Wait-list....who knows Grad Cafe Decisions IO.pdf

I emailed my POI on the 3rd of Jan, and he's accepted one person but also emailed me that they were still making decisions. I've lost hope. The world is so dark now.

So can we agree that Rice, NC State, UMD, Wayne State, UGA, Tulsa, and Northwestern have sent out their results?

@cupofsugar awesome job! If you have any ideas in regards to cleaning up the character columns let me know.

This happens in academia far too often. You could have near-perfect GRE scores, GPA, letters of recommendation, and even fit; yet you're still not selected. Social capital is a powerful thing, I wish there was more research on it. I worry when applying to programs that also have a terminal masters because of how often schools transition (though deserving) students from the masters to PhD program. Faculty of a student that know other faculty. Students finding their POI at a conference and getting face-time...they are playing the game. In IO we learn about how the most random factors like name and handshake can affect your likelihood to receive a job offer, especially when the process is unstructured. The application process is very unstructured: some professors hate the GRE, some love applied experience, some publications, sometimes it's just random in terms of who you apply to. It's hard not to take it personal. Graduate applicants are conscientious; you can tell by the path they've chosen. However, I've never met someone intrinsically motivated that didn't get in. Keep hope. Learn. Find out what the accepted candidates "had" that you didn't. Objectively you may have been much higher on the list, but the list isn't objective; otherwise, a computer would select who gets in. In reality: I cry and listen to Katy Perry's "The One That Got Away"

I was in a similar situation debt-wise. My MS actually was pretty cheap because of my assistantship (my tuition was waived both years). However, I'm only talking about my experience, but there is a good chance you can find a similar program. I'd say an MS in IO will get you a 65 to 70k salary first year out.

I wish you were a professor, preferably at one of the school in my signature. In all honesty, thank you for being so kind. I wish you the best of luck too. People love Nutella.

I'm doing it. In psychology, I feel this is very common. Clinical programs need methodologists, I/O's need social psychologists, cognitive needs neuro- the list goes on. Programs are looking for fit but they also are looking for intellectual curiosity. The biggest concern should be your own. As long as you can find an area that you're passionate about within the program, and you know the programs can support you- go for it.

I'm just going to drink beforehand... ...water. Hydration is good for cognitive processing.

After a short hiatus (to maintain my sanity) I've updated some things! Cleaned Institution and Program - the past few days have been rough. I've realized what kind of garbage fire the Institution and program data from the results survey is. I emailed grad cafe in hopes they would standardize the text inputs for the aforementioned columns. You'd be surprised at how many different ways someone can type in "UCLA". Hopefully the data is more accurate but there is still a lot to do. Added more graphics. I've split the decision plots by clinical, not-clinical, and everyone combined because who cares about clinical applicants? Kidding. Their apps tend to be due a lot sooner, you can see this in the plots. I've also added result by day of the week thanks to statisticalsleuth's suggestion. Further there is a table of the top schools that adds Rejection postings as a % of total postings (I removed postings involving other). R nerds: added a function file behind the R code so the script wouldn't be so overwhelming...though it's still overwhelming. This file is necessary for running the script (see the script here). I've also added an index of schools and programs for the string matching algorithm. ALL OF THESE FILES NEED TO BE IN YOUR Working Directory for the procedure to run. Finally I wanted to thank everyone for being supportive and giving me ideas. Best of luck during interviews! I've attached the PDF. You can also view it here. It's almost over.... Grad Cafe Decisions.pdf

What did your faculty, lab, or person of interest (POI) attribute to your success? If you don't have that information, what do you think did it? You don't have to be humble.

The applicant from NC State messaged me. They were accepted by my POI, so it was a bit of a bummer. I'm going to message him anyway because he may be getting 2 students. Regardless, really nice person and they deserve it.

Best and Craziest: Find a 9-to-5 job. Spend my nights crying myself to sleep, but capture my tears. I'll save my tears until I can fill a bath tub. Proceed to bath in my tears, but record it and post it on social media. The post will go viral, igniting my YouTube career. In my videos, I'll call out all those who've rejected me in the past; though I will still cry myself to sleep at night.

I fixed the "closer look" plot- ordering from Nov to May. Also, all I added a Program Type table on page 2. Be skeptical of all the program/school info due to the lack of clean data. I'm working in a string-matching function now, in hopes that I can get more accurate numbers related to those variables. I don't want people to worry if they missed a peak day. I estimate around half of the sample is Clinical Psych, which (to my knowledge) tend to have a few November deadlines, this will skew the data a bit. Updated version Thanks everyone for working on this with me!

The NC State candidate must've really impressed someone given that the app deadline was the 1st of Dec and they got an acceptance email on the 13th. My POI told me to email him in early January (when he starts to look at applications). This makes me nervous...

Thank you! Hopefully it helps But... This code is not clean, it's functional, it works but don't use it to impress anyone-- they may heckle you

I've updated the code and added some "School" stuff (the school variable was also not the cleanest). I question my text-cleaning ability, so that is an area for improvement. Here is a table of the data.frame @psych0 : I've attached the scraping portion (if you want to add more context please look at the R code) I'll also work on flipping the dates, R doesn't like date extraction as much but I'm sure I can find a workaround. Best, Scrape Grad Cafe.txt

Hello everyone, I've seen quite a bit of chatter around the timing of results, and the answers are obscure. I wanted to provide my services, and give you all some extra data. The beauty of grad cafe is that it is one of the most (if not the most) centralized data source for graduate students. Some data examples: What schools are most popular, what degrees, applicant metrics, dates of results, etc. Yet, I've yet to find someone that uses this information to help those applying. Until now... I used R (for those unfamiliar) to scrape the grad cafe results data related to psychology. I returned about 35000 records. There were a lot of un-tidy text strings (e.g., PhD and Ph.D.), especially in relation to program-title and institution; however, that is a project for another day. Data regarding dates and decisions did seem clean enough for me to analyze it and turn it into something nice for you all. So what is it....? Here is a PDF based on the results of all Psychology students (over 35000) since the origin of grad cafe. The first 3 tables show the 10 most common dates (by count) for getting an interview, getting accepted, and getting rejected ? . I would do relative frequency and should've...maybe tomorrow. Then a longitudinal line graph (which shows these decisions throughout the year) Finally, one that focuses more on the "critical-period" when most decisions are made. Conclusion This was a piecemeal job that I should be done in R Markdown. I'll link my code at the end. Similar methods could be used to look at the "most popular" programs, probability of acceptance by degree type or program type, average GRE score for accepted candidates, and the list goes on. If anyone wants a csv of the dataset I used, please feel free to message me. I also welcome critiques and suggestions. I wish you all the best. R code here

Here comes the anxiety...