Here's my understanding based on the article alone; would love corrections if I'm wildly missing the mark here.
Let's say you want to determine if a coin is fair, but you don't know any statistics. What you can do is write a program (model) that represents the fair coin flip process. It might be as simple as:
flips = [random.choice([True, False]) for x in range(0, 10)]
Then you flip your coin 10 times and feed the output into your program, and it gives you some indication of the probability that the coin is fair.
seemingly the program is also run backwards. so maybe it will try coins with various biases until it determines the model that gives the fair flipping?
i am speaking from what i gathered reading the article and the other comments. seems pretty interesting to me.
Let's say you want to determine if a coin is fair, but you don't know any statistics. What you can do is write a program (model) that represents the fair coin flip process. It might be as simple as:
Then you flip your coin 10 times and feed the output into your program, and it gives you some indication of the probability that the coin is fair.