Exercises: Decide if a Model Is Consistent with Data Using Simulation
Work through each section in order. A "model" is an assumed chance
mechanism (for example, "this coin lands heads with probability 0.5").
To decide if data is consistent with a model, assume the model is true,
simulate the data-generating process many times, build the simulated
distribution, and see how often the model produces a result as extreme
as the one observed. Remember: a surprising result is EVIDENCE to
question a model, never proof the model is false; and an ordinary result
never proves a model true.
Fluency Practice
Apply the simulation framework: device, trial, statistic, repetitions, and reading distributions.
A model says a spinning coin lands heads with probability . Rank these results from LEAST surprising to MOST surprising under this model: getting 3 tails in a row, 5 tails in a row, 10 tails in a row.