Curated List of 118 Blog Posts for Learning Statistics

This article presents a curated collection of 118 free blog posts designed to help readers learn about statistics, a fundamental science for data analysis and decision-making. The posts are organized based on HackerNoon reader engagement data, ensuring high-quality and popular content is prioritized. The collection covers a diverse range of statistical and machine learning topics, including loss functions like crossentropy and logloss, techniques for outlier detection, and the application of radial basis functions in predictive modeling. It also features practical guides on using pre-installed R datasets for statistical analysis, retrieving player statistics from the NHL's undocumented REST API, and advanced feature engineering methods for time series data such as Fourier and wavelet transforms. Additionally, the list includes technical implementations like Gaussian blurs and financial models like the Fama-French three-factor model. Readers are directed to the Learn Repo on GitHub or LearnRepo.com to access these resources and find other technology-related articles. This compilation serves as a comprehensive educational hub for developers, data scientists, and enthusiasts looking to deepen their understanding of statistical concepts through community-vetted tutorials and explanations.