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#4aa2821 @ Intermediate Apr 12, 2026

The Random Walk: From Coin Flips to Stochastic Calculus

Discover how a simple coin flip evolves into the mathematics powering modern derivative pricing. From Binomial Trees to the Wiener Process and the Heat Equation; we handle all in Python.

$ view source --file finding-p-values-and-false-hope/9-random-walk.md _
#7c05fec @ Advanced Mar 8, 2026

Is Sweet Bonanza 1000 Rigged? A Statistical Analysis of 60,000 Spins

We analyze 60,000 spins of Sweet Bonanza 1000 using Python, Bootstrap CI, and Hypothesis Testing to see if the 96.53% RTP holds up against extreme volatility.

$ view source --file expected-riches-and-expensive-lessons/2-sweet-bonanza-1000.md _
#73a6af1 @ Intermediate Mar 1, 2026

Value at Risk (VaR) vs. CVaR: A Practical Guide for Investors

Stop using abstract volatility. Learn how to calculate Value at Risk (VaR) and Conditional VaR (CVaR) using Python to understand your actual downside potential.

$ view source --file finding-p-values-and-false-hope/8-var.md _
#3ed9ce9 @ Advanced Feb 22, 2026

A Python-Based Statistical Audit of Gates of Olympus

Using Python, statistics, and 40,000 spins to analyze RTP, variance, bonus frequency, and volatility in Gates of Olympus through hypothesis testing and simulation.

$ view source --file expected-riches-and-expensive-lessons/1-gates-of-olympus.md _
#6beed8e @ Intermediate Feb 15, 2026

Stock Options 101: A Guide to Calls, Puts, and Pricing

Unlock the basics of stock options. Learn the difference between calls and puts, American vs. European styles, and how Greeks like Delta and Theta impact pricing.

$ view source --file finding-p-values-and-false-hope/7-options.md _
#25fa5b4 @ Beginner Feb 8, 2026

The Visual Storyteller: Mastering EDA with Seaborn and Python

Turn raw data into actionable insights. Learn how to use Seaborn and Matplotlib for Exploratory Data Analysis (EDA), including heatmaps, Q-Q plots, and distribution analysis.

$ view source --file data-science-with-python/3-visualising.md _
#690a342 @ Intermediate Feb 1, 2026

Portfolio Allocation: The Math Behind the Efficient Frontier

Master the quantitative core of Modern Portfolio Theory. Learn how to use Markowitz optimization and Python to build an efficient frontier for asset allocation.

$ view source --file finding-p-values-and-false-hope/6-allocation.md _
#7778373 @ Beginner Jan 25, 2026

The Cleaning Machine: 6 Steps to Trustworthy Data with Pandas

Master the 6-step framework for data wrangling. Learn to handle missing values, remove outliers using IQR, and validate data quality using Python and Pandas.

$ view source --file data-science-with-python/2-cleaning.md _