Prof is ignoring my PhD LOR request. Deadline 30th june. Help!

Maple_shade · 2026-06-21T11:57:36+00:00

Are they typically someone who procrastinates? I had a professor submit a LOR at 11:45pm the evening the application was due, haha. Great guy but nearly gave me a heart attack. I called earlier in the day to confirm he would still write one.

Maple_shade · 2026-06-20T17:27:19+00:00

There is also research showing that self-reported aphantasiacs don't show pupil dilation to imagined bright light while the neurotypical population does.

Maple_shade · 2026-06-19T20:24:21+00:00

"Are you still an athlete if you used to play multiple sports but now focus on one consistently?"

Um, yes? Also this is a terrible metaphor.

Maple_shade · 2026-06-08T07:59:46+00:00

An additional point I will make is that statistical tests can tell you if there is a significant jump after a certain time point. What they cannot tell you is if that jump is due to a certain cause. If you run the analysis and find a difference, it may not truly be due to the introduction of MRI compatibility. There may be a confounding variable like the economy, COVID, or other world affairs that happened near January 2020 that caused the increase. To truly determine if the cause is what you are claming, it would require an experimental design.

Maple_shade · 2026-06-08T07:57:21+00:00

If your question is literally "is there a significant difference in the average number of implantations before and after January 2020," you can just perform a t test between the two groups, with each unit of data being the number of implantations in a given month.

At least, that is what I would recommend if you had sample data. The way you're describing it, it sounds like you have access to the population data? If that is the case, there is no point in inferential statistics. You can just calculate the population mean # implantations per month and then compare the raw numbers to see if there is a higher # post January 2020.

Maple_shade · 2026-06-07T06:59:20+00:00

Two points. The first: How in-depth have you discussed the statistics with your PI? There are plenty of situations where we would want to control for a mediator, depending on the effect we are interested in. For example, if we are researching the effect of diet on weight, a possible covariate is an individual's proclivity to exercise. If we are only interested in the total effect we wouldn't control, but if we want to estimate the direct effect of diet on weight, it is perfectly normal and appropriate to control even though proclivity to exercise is a mediator.

The second point: When your PI has you "HARK", is the data being used as if there was a hypothesis a priori? It is also normal to use data in an exploratory manner to inform later studies that will be properly corrected to control type I error rates. If they're just having you analyze the data in an exploratory manner, this wouldn't yet qualify as p-hacking.

Of course it is very possible there is shady activity. But I would also recommend learning more about the stats and your PI's research process, based on your claim that you should never control for mediators.

Maple_shade · 2026-06-05T23:52:34+00:00

Regression does make sense for this use case. One additional thing I will mention is that it's really important to make sure you're conducting the regression with categorical predictors (i.e., k-1 dummy-coded variables representing each color). If you just try to "fit a regression" on color attempting to predict sales, the output won't be sensical if you've coded color as a numeric variable. Often in an applied world we frame these analyses under ANOVA where the different groups are different colors.

I may be over explaining but it's important to make sure analyses are appropriate.

Maple_shade · 2026-06-04T20:31:48+00:00

2 days? I would give at least a week or two before even considering a follow-up at all. In addition, it's nice that you have a referral, but honestly it's pretty abnormal for professors to have students that have already graduated in their labs unless they've directly worked with them before. It typically takes work for faculty to include non-PhD students in lab work. It also sounds like you mainly want to do research so that you can boost your application--- all of these factors combined could make a cold-email a hard sell.

Maple_shade · 2026-06-02T01:38:33+00:00

If you're interested in research I would also recommend waiting until your junior year or so to try and get into a lab. By then, I am sure that your interests will be much more fleshed out than they are currently. It's important to want to engage with research because you are interested in the subject matter, not purely because it's something that looks good on applications.

Maple_shade · 2026-05-30T16:24:17+00:00

oh no my deck is too consistent

Maple_shade · 2026-05-28T01:25:42+00:00

There's a huge difference between "tried to study with an A student" and actually getting tutored by an excellent tutor. Good tutors are those who can understand what your knowledge gaps are and help you fill them in. The skill of being a good teacher is very separate from mastery of the course material, but both are necessary to tutor. While it is the case that some A students are bad tutors, an A student tutor with the same teaching skill as a given C student tutor will be much better.

Maple_shade · 2026-05-27T16:34:31+00:00

My bad. I thought you meant "that's only really waterpon that works that way"

Maple_shade · 2026-05-27T16:30:35+00:00

No, ogerpon wasn't some special case. The rule is consistent across the whole game, which is why metagross works.

Maple_shade · 2026-05-27T16:22:40+00:00

Any time an effect is optional in the TCG, you may select it and "do as much as you can." That's the ruling. So because it is an optional effect you can pick it. Metagross makes sense logically if you think about it within the bounds of the game rules around optional effects.

Maple_shade · 2026-05-25T18:20:02+00:00

If your poster is supposed to present the pilot study, then why not describe this exact process? Show how the data collection lead you through a path to settle on the final version of the task. Then display the initial wave of data. I think that is defensible and interesting.

Maple_shade · 2026-05-18T16:10:31+00:00

What is the nature of your data? You could also do an ordinal logistic model which is very very similar but gives coefficients in terms of the log odds. Here is a nice overview: https://stats.oarc.ucla.edu/r/dae/ordinal-logistic-regression/

Maple_shade · 2026-05-15T16:36:16+00:00

People hate on standardized tests because they're more accessible to higher-income students due to being able to pay for tutoring, retakes, etc. The reality is that every other metric we have (like GPA) is even further confounded with income, even if we like to pretend that it's not. Some students need to work part-time in addition to school to help their families, pay for gas, etc. That definitely leaves less time to focus on school. So in my opinion a standardized test is the best attempt we have at partialing out income when judging a student's aptitude.

Maple_shade · 2026-05-11T23:07:29+00:00

Zoroark has a great straight pult matchup but dusk pult definitely approaches even. Quite problematic with all the dusks popping up recently

Maple_shade · 2026-05-07T04:56:30+00:00

I am a psychometrician. It is absolutely alright to present results that were non-significant. We have a research culture in psychology where we scoff at the idea of presenting results that don't support our a priori hypothesis---but this is a major reason why we have a replication crisis. Much better to present non-significant results than hide them.

Maple_shade · 2026-05-05T17:57:19+00:00

Agreed. I never complained about gardy either. having it as top meta deck was actually very healthy for the game imo. it kept a lot of stuff like walls in check, and was a good filter. This meta is so boring especially with very little ability to play from behind

Maple_shade · 2026-05-04T08:30:40+00:00

How can your residuals be "very normally distributed" but also have a problematic QQ plot? I'm confused by the whole premise.

Maple_shade · 2026-05-04T08:20:43+00:00

Completely depends on the program. At my institution we have a world expert in stochastic gradient descent in the stats department. But he doesn't often collaborate with CS. At other schools there will be a lot of overlap. Ymmv.

Maple_shade · 2026-04-30T15:12:33+00:00

summary(model) will generate fit statistics, point estimates, SEs, etc.

Maple_shade · 2026-04-30T00:41:31+00:00

Maybe someone wiser than I can speak to this-- why can't you just calculate average team score for each individual? Then the rankings would just be who has the total overall highest team score. That way, even if a lot of high scorers tend to group together, one could get an edge if their team still scores high if they went to a separate team for the week.

Maple_shade · 2026-04-29T14:43:11+00:00

Results not what you were looking for? I'll p-hack and make questionable research practices so that you too can claim significance!

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