How one random sample gives a confidence interval for a population mean, using the standard error σ/√n, the sample SD as a proxy, and MIT 6.0002 code.
2026, Oct 26 — 26 minute read
MIT 6.0002 Lecture 5 in Python: Location, Field and Drunk classes, a sanity check that caught a bug, and why a random walk drifts √n away on average.
2026, Oct 26 — 29 minute read
Monte Carlo simulation with roulette: exact returns of 0, -1/37 and -2/38, the law of large numbers, and 95 % confidence intervals from the empirical rule.
2026, Oct 26 — 30 minute read
What users lose when a HIP-1 to HIP-4 market fails on Hyperliquid, how to judge a market before trading it, and worked examples for each proposal.
2026, Oct 26 — 26 minute read
Twelve flashcards for Hyperliquid HIP-1 to HIP-4: native tokens, Hyperliquidity, builder-deployed perp DEXs, slashing and outcome markets, with a revision table.
2026, Oct 26 — 11 minute read
Request payloads, info queries, asset-ID lookups, error cases, testnet steps and checklists for deploying and integrating Hyperliquid HIP-1 to HIP-4.
2026, Oct 26 — 28 minute read
Graphs as models, adjacency lists in Python, and why breadth-first search finds the fewest-edge path but not the cheapest weighted one.
2026, Oct 26 — 33 minute read
