In statistics, the definition of a p-value is this: The p-value is the probability under the hypothesized model of a statistic at least as extreme as the one observed. Use your output to calculate a p-value in this example. Hint: The "hypothesized model" here is that the flips are truly random and independent. Your histogram in step 4 therefore represents the probability distribution of the statistic under the hypothesized model, so your p-value should equal the fraction of that histogram at least as extreme as the point represented by the red dot. In this case, "extreme" could be interpreted to mean far away from the histogram's center in either direction, but since this concept is new in this class, it's okay here if you simply calculate the proportion of your histogram in the smaller part that is at least as extreme as the observed statistic