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.
Warm-Up: Models, Chance, and Distributions
These problems review ideas you already know about chance and distributions.
A simulated distribution of the number of heads in 10 flips of a fair coin centers at its expected value. For a fair coin (), the expected number of heads in 10 flips is . About what value does the center of the simulated distribution sit at?