This should be all we review, we introduce it in other videos. We have seen in other videos if our p-value is less than our significance level, then we reject, reject our null hypothesis. And if our p-value is greater than or equal to our significance level, alpha, then we fail to reject, fail to reject our null hypothesis. And when we reject our null hypothesis, some people say that might suggest the alternative hypothesis. And the reason why this makes sense is if the probability of getting this statistic from a sample of a certain size, if we assume that the null hypothesis is true, is reasonably low, if it's below a threshold, maybe this threshold is 5%, if the probability of that happening was less than 5%, then hey, maybe it's reasonable to reject it. But we might be wrong in either of these scenarios, and that's where these errors come into play. Let's make a grid to make this clear.