r/AskStatistics

I have a random question/situation. I was speaking to someone who runs a business, and they have massive data sets -- it's athletics based, but you would have literally millions of data points, and presumably a ton of subsets.

Aside from GAMBLING -- please -- are there any academia uses or a/b tests that would make that data useful. I guess, when he said a professional company's data set is worth more than it's tv rights, it got me thinking that potentially there is a way to use his data in statistical testing that makes it valuable.

Does this make sense? Like are there cross-professional or random data sets that are valuable outside of their intended specific use?

Considering how AI "takes over" mathematics right now, is grad school in statistics still worth it if I want an academic career?

Since the start of season 40, the mystery wedge has been flipped 128 times.

85 times it's been a bankrupt

43 times it's been $10,000

Assuming a fair 50-50 chance, the chance of that happening is 0.01293%.

In order to regress to the expected mean, it would have to be $10,000 the next 42 times in a row. Such poor luck!

I (f20)am on my 3rd attempt at psych statitsistcs. still nothing is clicking for me. I’ve asked for help, I’ve gone to tutoring and nothing seems to work. I spent two straight days going through all of the lectures so far to study for the midterm and a quiz I had to take. I got a 40% on that quiz and I got a 26% on my last quiz.. I’m currently failing the class. To pass, you need to C or above. I’d like to drop out, but my mom will not allow it so I feel like I’m going to keep failing this class to no end.

So if any of you have any recommendations for Youtubers or something that could possibly help me, that would be nice. I understand standard deviation but everything beyond that makes zero sense to me.

I don’t understand z scores or Z tables, confidence intervals, Alpha levels, sampling error, standard deviation of sample means, etc. I know I’m too stupid for college, but I am not allowed to drop out so I need to figure something out.

I also don’t understand hypothesis testing or any kinds of T-tests

I'm preparing POET II for a journal club (open-label RCT of response-tailored vs standard antibiotic duration in left-sided endocarditis, NEJM, Aug 2026) and can't reconcile the sample size with the stated confidence level.

Stated in the paper and supplement: safety endpoint, non-inferiority, assumed event rate 8%, margin 7.5 points, 90% power gives 450 patients, "with a one-sided confidence interval of 97.5%". Per pathogen: margin 12.5 points, 80% power gives 118 patients.

My check, using n per arm = (Zα + Zβ)² × 2p(1−p) / Δ², with p = 0.08 and no true difference:

	Overall (Δ 7.5, 90% power)	Per pathogen (Δ 12.5, 80% power)
One-sided alpha 0.05	224 per arm (~450)	59 per arm (118)
One-sided alpha 0.025	275 per arm (~550)	74 per arm (~148)

Only alpha 0.05 reproduces the stated numbers. The 2020 design paper (margin 5%, 80% power, "alpha 5%") gives 730 patients, which also fits one-sided 0.05 (about 924 at 0.025). The results report two-sided 95% CIs (equivalent to one-sided 97.5%), so the analysis is stricter than the calculation. By my numbers, power is then about 83% overall (about 88% with the 508 randomised) and about 70% per pathogen.

Questions:

1. Is there a standard variant (continuity correction, variance under the null, software default) that gives 450 and 118 at one-sided 0.025? I couldn't find one.
2. If it is just a labelling slip, would you treat it as a minor wording issue or a real power issue in an appraisal?

Hi, I am trying to finish up my psychology thesis! I am in a bit of a rut trying to compare my results of a binary logistic regression with previous literature. However, there is a very limited amount of literature in my current area of study; I have only one study that used the same variables I did. They used a multiple logistic regression analysis, and I used a binary logistic regression.

I am just wondering what the main difference between the two models is and if I can interpret my results in comparison to this prior literature I have found.

Thankyou!!!!!

Hi, I have a stats master but been quite long away from this, so need some good reasoning.

I have 100 subjects, 4 variables, and want to evaluate their effect on 1 year survival. I have no censoring, i.e. I know for.sure for everyone whether they died or not within this year. Number of events is 30. The issue is tgat for one of the variables I suspect that the effect starts only after a few months, although with this sample size I failed to reject H0 about the PH violation.

I then fitted logistic regression to see whether they died whithin this one year.

What is the difference in such logreg and cox in this case? Statistically and with interpretation.

Please throw everything on me, I just have to recall it, it has been a while unfortunatelly....

-Bootstrapping

-Trim fill method

-P hacking

-Simpson's paradox

-Collider bias

--Stat significance

-Longitudinal vs cross sectional

-Meta analysis vs systemic review

Bonjour. Si cela vous est possible, j’aimerais solliciter votre aide et avoir quelques renseignements concernant l’utilisation du logiciel R.

Je dispose d’une base de données comprenant des variables numériques, ordinales et binaires. Je souhaiterais standardiser mes données afin de réaliser une analyse factorielle.

Je voudrais savoir si je dois utiliser la commande digital.std <- scale(digital) pour l’ensemble des variables, ou s’il est préférable de procéder différemment selon le type de variables, notamment pour les variables binaires et ordinales. Quel est la manière correcte??

Je vous remercie par avance pour votre aide.

If you like computational statistics and love reading on advanced statistical methods, what jobs are for you, especially if you can’t get a master’s?