Discover advanced feature engineering techniques for time series data, including Fourier transform, wavelet transformation, derivatives, and autocorrelation.

E-commerce is a promising business area that shows high growth rates each year.

Bonferroni correction as a solution for multiple comparisons problem in A/B tests. Here is an explanation of how it works with a simulation written in Python.

A quick walkthrough of the three frameworks in probability viz. classical, frequentist and Bayesian through an example.

Principal Component Analysis (PCA) is a statistical technique used for dimensionality reduction in data analysis and machine learning.

As we wrap up our journey into the world of lottery data, it's been a wild ride through numbers and probabilities.

Learn how web scraping and data aggregation might feed of each other, unintentionally creating an effect of decision-making convergence.

Learn everything you need to know about Statistics via these 70 free HackerNoon stories.

This series of articles covers the techniques and gyan on winning in skilled games which are variants of Roulette, Wheel of Fortune and Baccarat.

Decisions are usually based on the sample mean, which is very sensitive to outliers and can dramatically change the value. So, it is crucial to manage outliers

In this article, we will explore practical implementation with Python code and interpretation of the results.

I've started playing around with publicly available polling data for the 2024 U.S. presidential election.

From some general data to liquidity providers' (LP) reward lists, let’s explore some handy Obyte-related portals.

Our algorithm can also be modified slightly to obtain a fully adaptive algorithm with sample complexity O˜(log log n).