Articles, newest first
Understanding Value at Risk (VaR) and Its Types
A detailed exploration of Value at Risk (VaR), covering its different types, methods of calculation, and applications in modern portfolio management.
Read article
Maryam Mirzakhani: Geometry and Dynamics of Moduli Spaces
Maryam Mirzakhani transformed the geometry and dynamics of moduli spaces through work on simple closed geodesics, Weil-Petersson volumes, earthquake flow, an...
Read article
Understanding the Fowlkes-Mallows Index: A Tool for Clustering and Classification Evaluation
The Fowlkes-Mallows Index is a statistical measure used for evaluating clustering and classification performance by comparing the similarity of data groupings.
Read article
Understanding Mean Time Between Failures (MTBF)
Explore the key concepts of Mean Time Between Failures (MTBF), how it is calculated, its applications, and its alternatives in system reliability.
Read article
Chi-Square Test: Testing Categorical Data
The Chi-Square Test is a powerful tool for analyzing relationships in categorical data. Learn its principles and practical applications.
Read article
Advanced Statistical Methods for Efficient A/B Testing
An in-depth exploration of sequential testing and its application in A/B testing. Understand the statistical underpinnings, advantages, limitations, and prac...
Read article
Walking the Mathematical Path
Dive into the fascinating world of pedestrian behavior through mathematical models like the Social Force Model. Learn how these models inform urban planning,...
Read article
Error Terms in Linear and Logistic Regression
Linear and logistic regression encode randomness differently. The distinction is between an additive disturbance model and a Bernoulli conditional distributi...
Read article
Understanding PCA: A Step-by-Step Guide to Principal Component Analysis
Learn about Principal Component Analysis (PCA) and how it helps in feature extraction, dimensionality reduction, and identifying key patterns in data.
Read article
Simpson’s Paradox: Theoretical Foundations and Implications in Data Analysis
Simpson's Paradox shows how aggregated data can lead to misleading trends. Learn the theory behind this paradox, its practical implications, and how to analy...
Read article