00:02
So we have some statements here we want to determine whether they are true or false.
00:07
So let's look at the first one.
00:10
So it says that the sample correlation coefficient is equal to a covariance divided by the square root of the product of x squared over x y squared.
00:23
So let's see.
00:23
So we know that the correlation coefficient r that is given by the summation x i minus x bar y i minus y minus y bar divided by n minus 1 the sample coefficient divided by the square root of minus 1 into summation x i minus x bar squared times 1 over n1 minus 1 excuse me summation y minus y bar all squared what is this so the numerator that is just the covariance of x and y and the numerator so if you look like just this portion okay that is just uh this is square root so that portion is just x squared and the other side which is this is x y squared and so that is a that is true okay let's see what b is so for b it's an r value of point mine indicates a strong negative correlation coefficient so we know that r is always lies between zero and i'm sorry negative one and one right so we have an r value so we've been given r equals negative 0 .9.
03:00
What that means is that, of course, if r is 1, that's a high positive correlation or strong.
03:20
And if r is negative 1, that is high negative, oops, that's a high negative correlation.
03:38
And so for r equals negative 0 .9, that's a bit.
03:48
Indicates a strong correlation.
03:59
It's a strong negative correlation.
04:09
So that is also true...