00:01
So here we want to compute the pearson correlation coefficient, which is given by r equal to the sum of the difference of each x sub i's minus their means times the y's minus their means, all over the square root of the sum of the x sub i minus their means squared, and then times the square root of the sums of the y's minus their means squared.
00:34
So here we have height and weight variables, so we're going to let the x be our heights and then our y be our weights.
00:43
So the heights have the following values, we have 61, 60, 51, 59, and 59, and the weights have the values 54, 79, 109, 97, and 82.
01:06
So we need to go ahead and find the means, so h bar is then going to be 61 plus 60 plus 51 plus 59 plus 59 all over 5.
01:19
And when we find that mean, it's going to equal 58.
01:23
For the weight, we're going to take 54 plus 79 plus 109 plus 97 plus 82 and divide that by 5 to get a mean equal to 84 .2.
01:38
So now let's go ahead and calculate our values needed.
01:42
So we're going to take our h minus h bar and then our weight minus our mean, and then we're going to do the h minus h bar squared and repeat the same thing for the weights.
02:08
Alright, so then let's go ahead and find these.
02:11
So you're going to take each h and subtract it from the mean, so you're going to start with 61 and subtract 58, that is equal to 3.
02:19
Then 60 minus 58, which equals 2.
02:24
And you can repeat this for the rest of your h of i's, so the 51 minus 58, the 59 minus 58, and the 59 minus 58 to get values of negative 7, 1, and 1.
02:38
And you can repeat this with the weights...