Animated explanations of the math behind economics and business — built so the idea arrives first and the formula second.
Four chapters so far, walking from ratios up toward multivariable calculus. One chapter, one way of seeing.
A video is a bad place to answer a specific question. These pages answer one each, with the answer up front.
Type z = f(x, y) and a 3D island becomes that graph. Runs in the browser,
no install.
Newest chapter
A vector is a building block for movement, and its coordinates are just how many times you use each block. Know where the basis vectors land, and you know where everything lands.
The series
The minimum math you need, explained intuitively. Each chapter installs a schema — a way of seeing — rather than a procedure to memorise. They build on each other, but each one stands on its own.
A ratio is the size B would have if you called A's size 1. A percentage is the same idea with 100 instead — and crucially, it needn't be a slice of a whole.
Set the input nudge to 1 and the output nudge is the derivative. That's all df/dx means — and it's exactly what "marginal" means in economics.
An angle is the length of the arc it cuts from a circle of radius 1. Sine and cosine are the two heights you climb walking a distance of 1 from the origin.
Vectors as building blocks for movement, and transformations that move the whole space at once.
Open World Discover
A 3D open world that runs in your browser, where the island is a function. Type
z = f(x, y) and the terrain becomes that graph — then drive, fly, or walk
across it.
Read instead of watch
You can't skim a video, and you can't quote one. So the ideas also live here as writing — one concept per page, with the answer in the first paragraph.
Why a percentage is allowed to pass 100%, and what separates a ratio from a proportion.
Marginal cost is dTC/dQ — and MR = MC is the first-derivative test in a
business suit.
Why a 15% treadmill incline is about 8.5°, not 15° — and why grade and degrees drift apart as the hill steepens.
What a basis vector is, and why the columns of a matrix are simply where the basis vectors landed.
