1 00:00:00,250 --> 00:00:05,370 One common measure of affect size, when comparing means, is Cohen's d. Named 2 00:00:05,370 --> 00:00:10,300 after the statistition Jacob Cohen. Cohen's d is a standardized mean difference 3 00:00:10,300 --> 00:00:15,562 that measures the distance between 2 means in standard deviation units. In 4 00:00:15,562 --> 00:00:19,559 other words, instead of dividing by standard error. We simply divide by the 5 00:00:19,559 --> 00:00:23,918 standard deviation of the sample. We can think of it like this, we have our 6 00:00:23,918 --> 00:00:29,551 sample, let's just say it's normally distributed. And here's the sample mean, 7 00:00:29,551 --> 00:00:33,966 and the standard deviation of our sample is S. Now let's say we have some 8 00:00:33,966 --> 00:00:41,630 population mean out here. How many S's fit between x-bar and the mean? The 9 00:00:41,630 --> 00:00:44,780 larger Cohen's d is, the further x-bar is from mu-not, in terms of the sample 10 00:00:44,780 --> 00:00:50,353 standard deviation. So, go ahead and calculate Cohen's d for this example.