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Statistical distributions

Count the paths, and a shape appears.

Flip a coin three times and there are eight equally likely stories. Sort them by how many heads they contain and the binomial distribution falls out — no formula needed yet, just counting.

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Eight equal paths

Every route through the tree has probability (12)3=18\left(\tfrac12\right)^3 = \tfrac18. One path gives three heads, three give two, three give one, one gives none — the row 1, 3, 3, 11,\ 3,\ 3,\ 1 from Pascal's triangle in Chapter 7 of Pure.

Counts become heights

Gather the paths by their number of heads and the counts become heights. That is X∼B(3, 0.5)X \sim B(3,\,0.5): the coefficient counts the orders, and each order carries 18\tfrac18.

P(X=r)=(3r)(12)3P(X = r) = \binom{3}{r}\left(\tfrac12\right)^3

More flips

With 20 tosses there are over a million paths, but the same counting holds, and the shape settles into a hump around ten heads.

P(X=r)=(nr)pr(1−p)n−r\begin{aligned} &P(X = r) \\ &= \binom{n}{r} p^r (1-p)^{n-r} \end{aligned}

An unfair coin

Nothing about the argument needed a fair coin. Slide pp down to 0.3 and the pr(1−p)n−rp^r(1-p)^{n-r} does the rest: the hump slides left and leans, because low counts are now the likely ones.

Chapter 6

Four conditions, one formula, a calculator for the rest.

Discrete random variables, the binomial conditions, cumulative probabilities, judging whether the model fits, and twelve graded exam questions with full worked solutions are waiting.