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Great Reads

Beginning data clustering

by Andy Allinger

Introduces data clustering and the k-means++ algorithm

From Stationarity to Randomness through Chaos

by Miguel Diaz Kusztrich

Using R to explore complexity of time series generated by simple process

Implementation of Gauss–Newton Algorithm in Java

by Ata Amini

Implement Gauss-Newton algorithm in Java to solve non-linear least squares problems; i.e. to find minimum of a function.

Implementing correspondence analysis with C#

by Miguel Diaz Kusztrich

Complete algorithm for correspondence analysis to add to your own statistical class clibrary

Latest Articles

Beginning data clustering

by Andy Allinger

Introduces data clustering and the k-means++ algorithm

From Stationarity to Randomness through Chaos

by Miguel Diaz Kusztrich

Using R to explore complexity of time series generated by simple process

Implementation of Gauss–Newton Algorithm in Java

by Ata Amini

Implement Gauss-Newton algorithm in Java to solve non-linear least squares problems; i.e. to find minimum of a function.

Implementing correspondence analysis with C#

by Miguel Diaz Kusztrich

Complete algorithm for correspondence analysis to add to your own statistical class clibrary

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Statistical Outliers Detection: Worksheet Solution

by DrABELL

Statistical Outliers detection in Microsoft Excel worksheet using Median() and array formula

Unveiling the Counterintuitive Nature of the Monty Hall Problem - A Simulation-Based Investigation

by Jack Devey

This post delves into the perplexing Monty Hall paradox, examining the probabilities associated with sticking or switching doors in the game scenario.