00:01
Hey there, welcome to numerate.
00:02
So we are asked to compute the correlation coefficient here, given the linear relationship between x and y and their data.
00:10
So with this, our equation for the correlation coefficient equals, for the pearson's, are the sum of products, divided by the square root of the sum of squares of x, multiplied by the sum of squares of y.
00:34
So with this, our equation for the sum of products equals the sum of x minus its mean.
00:44
So i went on ahead and computed the mean for both x and y here, which is 5 multiplied by a y minus this mean, which is 11 .2.
01:01
With this, we're going to compute this and we get a sum of products that equals around 42.
01:07
Now we can also find the sum of squares of x, which is basically what we have here, but it's going to be squared.
01:23
Given us a sum of squares of x that equals around 16.
01:29
We can also find the sum of squares of y, which is the sum of y minus mean squared.
01:43
Give us a sum of squares of y that equals around 116 .8.
01:50
Plug in these values here back into our original equation.
01:55
So what we'll get is the sum of products equals 42 divided by the square root of 16, multiplied by sum of squares of y 116.
02:29
Point eight given us a value for the pearson correlation coefficient of 0 .9716.
02:42
0 .9716.
02:45
What be our answer here? okay.
02:51
Now moving on, so we have to determine by there is a linear relationship.
02:56
So this is a pretty strong linear relationship where it is positive.
03:02
That's your first place...