Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

David Harper is the CEO and founder of Bionic Turtle. He is also a published author with a popular YouTube channel on expert finance topics. Probability distributions help investors model uncertainty ...

Hardly anyone is interested in my tax return—there’s not much to it. And that’s a good thing, given that an attacker might have fairly easily intercepted the encrypted communication between my laptop ...

In the realm of probability and statistics, the binomial distribution serves as a cornerstone concept, shaping decisions across industries. It is essential for understanding scenarios with a fixed ...

in this video we'll look at an application of the probabilistic method to extremal set theory extremal set theory is an area of combinatorics concerned with questions such as what is the largest ...

Bayes factors represent an informative alternative to P-values for reporting outcomes of hypothesis tests. They provide direct measures of the relative support that data provide to competing ...

This library supports calculation of uniform boundaries, confidence sequences, and always-valid p-values. These constructs are useful in sequential A/B testing, best-arm identification, and other ...

Abstract: This paper is about Jacobi’s triple product identity and Euler’s pentagonal number theorem. To be specific, it gives the proofs of Jacobi’s triple product identity via Gaussian polynomials ...

The approximation proposed in NEBULA-LN provides asymptotically consistent estimates (Supplementary Note A.5). Nevertheless, it is crucial to assess its practical performance under a finite sample ...

Topological data analyses are widely used for describing and conceptualizing large volumes of neurobiological data, e.g., for quantifying spiking outputs of large neuronal ensembles and thus ...

Computational modeling and mathematical modeling provide an insightful quantitative framework that allows researchers to inspect latent processes and to understand hidden mechanisms. Hence, ...