Key concepts:
Regression to the mean: the big hits from Hollywood may be have been more luck than talents. Good luck in the beginning is better than bad luck in the beginning.

Monte Hall’s problem: The winning probability of switching to the unopened door of “Let’s make a deal” game is higher than not.

Applying multiplication vs. sum of individual probabilities. The availability bias causes us to overestimate probabilities of events associated with memorable or vivid occurrences.

Gerolamo Cardano’s sample space: including sequence of events like having 1 or 2 daughters for a set of fraternal twins. Interesting story about Gerolamo Cardano; how he went from rag (due to his despite for physicians) to riches (a famous physician and gambler). His demise and death at 75 was caused by his own son, trading up to a torturer job. His work (book on “Game of Chance”) on probability was not discovered until 100+ years after his death.

Pascal and his Pascal Wager and Pascal Triangle. Very informative description of calculating the sample space for the lotto.

The conditional probability: Author’s HIV test experience, athletes’ doping cases. Statistics used in OJ Simpson’s trial – how the attorneys twisted the statistics to bias toward client’s case.

Normal distribution: sample variances and error. Voters’ poll error.

Randomness being perceived as a pattern might be due to human nature of wanting to explain the cause and reasons.

This is a nice refresher book on statistics. I have learned a few things especially around the conditional probability. This is a tricky area for most people.