NishMath

This cluster discusses key concepts in probability and statistics, including hypothesis testing, descriptive measures of association, and the use of Monte Carlo simulations to estimate probabilities. It also touches on the importance of data and statistics in data science and how these tools are used to make informed decisions based on data. The topics range from basic principles to practical applications like Chi-squared tests and are essential for anyone working in data science or research. The discussions help build a foundational understanding of statistical methods in various fields.

This cluster explores the applications of probability and statistics, specifically how they are used in daily life and for data science. The articles cover various aspects such as understanding z-scores, building effective metrics, the relationship between data science and math, and the importance of probability and statistics in the field. The discussions also include how to quickly learn the fundamentals of statistics.

This cluster focuses on probability and statistical analysis, covering diverse topics such as counting techniques in probability, joint, marginal, and conditional probabilities, and the transformation of distributions. Additionally, it includes a discussion of practical applications of probability distributions, with examples from finance, and the analysis of error in variables models, which is very important in the real world.