0:00:00.250,0:00:05.370
One common measure of affect size, when comparing means, is Cohen's d. Named
0:00:05.370,0:00:10.300
after the statistition Jacob Cohen. Cohen's d is a standardized mean difference
0:00:10.300,0:00:15.562
that measures the distance between 2 means in standard deviation units. In
0:00:15.562,0:00:19.559
other words, instead of dividing by standard error. We simply divide by the
0:00:19.559,0:00:23.918
standard deviation of the sample. We can think of it like this, we have our
0:00:23.918,0:00:29.551
sample, let's just say it's normally distributed. And here's the sample mean,
0:00:29.551,0:00:33.966
and the standard deviation of our sample is S. Now let's say we have some
0:00:33.966,0:00:41.630
population mean out here. How many S's fit between x-bar and the mean? The
0:00:41.630,0:00:44.780
larger Cohen's d is, the further x-bar is from mu-not, in terms of the sample
0:00:44.780,0:00:50.353
standard deviation. So, go ahead and calculate Cohen's d for this example.