Statistics – Cantor's Archive

Probability Theory
Better-Than-Random Decisions in Uninformed Settings
Two envelopes with different amounts of money in them. Choose the better one with a higher chance than fifty-fifty!
Statistics
Do Masses of Fundamental Particles Follow Benford’s Law?
How a statistical test used to uncover tax frauds may help us find an explanation to a long-standing puzzle in particle physics
Statistics
Huber Loss: Why Is It, Like How It Is?
On the day I was introduced to Huber loss by Michal Fabinger, the very first thing that came to my mind was the question: “How did someone joined these two functions in a mathematical way?”. Apart from that, the usage of Huber loss was pretty straightforward to understand when he
Mathematical Modelling
The Time Evolution of a Particle’s Position
To determine the position of a particle can be a very challenging task. The obvious way is to look at it and see where it is at that time. However, as one can expect, measuring the position of a particle at every instance of time is very difficult (impossible). (A

Statistics
Maximum Likelihood Estimate
Part 2: Mixture Models
Probability Theory
Maximum Likelihood Estimate
Part 1: How to best fit a Gaussian
Chaos Theory
The Chaos of Weather Prediction
Since existence, humans have been trying to predict the weather. Early methods looked to astrology and the lunar phases. Even the Bible contains references to Jesus deciphering local weather patterns!
Statistics
Here’s What a Theft Taught me about Statistics and Probability
A statistics lesson that can help you protect your valuables

Applied Statistics
Everything You’ve Ever Known is Statistics
Information is never without uncertainty
Applied Statistics
The Binomial Distribution Explained
You guess all 20 questions on your multiple-choice exam. What are the chances that you pass?
Statistics
An Intuitive Explanation of Benford’s Law
A simpler way of visualising and observing Benford’s Law through the powers of two
Bayesian Statistics
What is Bayesian Statistics?
A single, basic example: fully explained.