statistics

Generally in most of the resources discussing deep generative models, we have to maxmize the log likelihood of a distribution using latent variable. $p(x) = \sum_z p(x,z)=\sum_zq(z)\frac{p(x,z)}{q(z)} ...

Mathematics readiness at entry remains critical for success in first-year engineering programs, yet many institutions lack transparent, reusable tools to diagnose risk and design levelling policies. This study develops and evaluates an open Engineering Mathematics Readiness Score (EMRS) using two publicly available datasets: the UCI Student Performance dataset in secondary-school mathematics and …

The note gives the exact genesis of the Knuth-Statistician debate. Statistical bound and its empirical estimate, Empirical O (Oemp), are fully explained with applications.

I have completed finishing Class 12 (CBSE) and plan to pursue a career in quant finance. I have about 2.5–3.5 months before starting undergrad. I wanted to ask: What should I focus on during this time to build a strong foundation? Which skills (math, programming, stats, etc.) should I prioritize? Any specific resources, projects, or habits that would give me an edge early on? Thanks!

thanks. and nice to see some people in here are still interested in options stuff. now research focus shall be on computing the IG quantile function more efficiently, i guess. Statistics: Posted by tags — 4 minutes ago

To the ancient Maya, time was not a straight line moving from the past into the future; it was a series of interlocking cycles, some short and some spanning millions of years. Their ability to track these cycles required a mathematical system far more advanced than what was being used in Europe at the same time. By combining a vigesimal (base-20) system with the concept of zero , the Maya created…

I’m working with summary statistics (means, standard errors, and sample sizes) for two variables, and I’ve derived: SD of variable A from its standard error and sample size The ratio (P = A / B ) ...

At the request of a reviewer who asked us to test for outliers, and at the suggestion of my research director who mentioned Grubbs’ test, I am trying to do Grubbs’ test as one of the approaches to ...

In statistics, the autocorrelation sequence (ACS) of a discrete-time stochastic process is typically defined in terms of an expectation. For example, as described in "Intuitive probability and ...

Five positive integers have median and mode equal, i.e. $5$. If we add three positive integers such that we have eight new data which have mode $4$, does median of eight new data always change? Let ...

Ok The reason I asked about variance of variance is that if you want it to be finite, then also E[sigma(z)] must be finite, and then your quadratic relation implies that E[z^2] is finite - so no heavy tails for returns IDK maybe this is a trivial observation, but it seems to me that it narrows down the scope of processes to consider. Statistics: Posted by ISayMoo — 8 minutes ago

A multi-line insurer writes auto, home, commercial property, and a dozen other policy types under one roof. Some lines see thousands of claims a year; others might see 50. Every actuary faces the same dilemma: train a separate pricing model for each line and the small ones are pure noise, or pool everything together and pretend a warehouse fire looks like a fender bender. Either way, you lose. Hi…

𝑘-Variance: A Clustered Notion of Variance Solomon, Justin; Greenewald, Kristjan; Nagaraja, Haikady We introduce 𝑘-variance, a generalization of variance built on the machinery of random bipartite matchings. 𝑘-variance measures the expected cost of matching two sets of 𝑘 samples from a distribution to each other, capturing local rather than global information about a measure as 𝑘 increases; it is…

Scientific Reports, Published online: 25 April 2026; doi:10.1038/s41598-026-46520-y Estimation of spatiotemporal poisson processes with missing data

Ten posts. Vectors. Matrices. Dot products. Matrix multiplication. Derivatives. Gradient descent. Statistics. Probability. Normal distributions. Every single concept explained. Zero of them actually running together in one place. Until now. This post is different from every other in Phase 2. No new concepts. No theory. Just code. Everything you learned over the last ten posts wired together in Nu…

This answer to a Code Review question about statistics in Java asserts that, when all values are floating points, computing the mean of several values as $\sum_{i=1}^n \frac{x_i}{n}$ will be more ...

Welcome to Carry the Two, the podcast about how math and statistics impact the world around us from the Institute for Mathematical and Statistical Innovation. In this season of Carry the Two we are going to be examining how math and stats intersect with the world of gambling. This episode is all about sports prop bets and parlays. Hosts Sam Hansen and Sadie Witkowski are joined by David Taylor ma…

It’s simpler than you think. The post Lasso Regression: Why the Solution Lives on a Diamond appeared first on Towards Data Science .

The BCa bootstrap interval can be understood not merely as a higher-order endpoint correction, but as a small piece of frequentist inferential geometry. We isolate a rigorous core for that interpretation. A simple exponential-tilt object built directly from jackknife data recovers the familiar BCa bias and curvature corrections exactly. The classical BCa adjustment is then shown to arise as the u…

IntroductionThis simulation study evaluated how model fit in multilevel structural equation models (ML-SEM) is affected by within-person nonuniform measurement bias in intensive longitudinal data (ILD). This kind of bias would be given if item discrimination (i.e., their factor loadings) in multiple-item questionnaires varied within person across time. Prior simulation studies and ILD studies ten…