This Lecture introduces important concepts in probability and random chance. Probability forms the basis of inferential statistics, a branch of the subject essential for hypothesis testing.
Probability is also vital for assessing the confidence of estimates.
The Lecture considers 'p' values and statistical significance. Statistical significance and everyday significance are not the same thing since 'p' values simply express the probability that samples are from the same population. Finally, we consider a class of statistical methods which are called 'Monte-Carlo' methods which allow you to compare real data with sets of simulated data to estimate 'p' values. If you are not sure of this material, check Pagano chapter 8. BUT The difference may not be important, AND important differences may not be 'statistically significant'.