00:01
In this question, we are being given the value of n is equal to 40.
00:06
Sample mean x -par is equal to summation of x -i divided by n, which is equal to, so we have sum of observations is equal to 220 divided by n, which is 40.
00:20
So we get the value of sample mean x -par is equal to 5 .5.
00:25
And we have y bar is equal to summation of y i divided by n so we have summation of y i as 130 divided by n is equal to 40 so from this we get sample meaning y bar is equal to 3 .475 now sum of squares of x s x is equal to summation of x minus x bar whole square so on calculating this we get the value as 370.
00:58
Similarly, the sum of squares of y, this is equal to summation of y minus y bar whole square.
01:06
On calculating this, we get this value as 147 .975.
01:12
Next we have sum of squares of xy.
01:15
This is equal to summation of x minus x bar times of y minus y bar.
01:22
So on calculating this, we get the required value as 133.
01:26
Point five.
01:27
Now finding the correlation coefficient so we have the correlation coefficient is equal to the correlation coefficient denoted by r is equal to sum of squares of x y divided by square root of sum of squares of x times of sum of squares of y so this is equal to negative 133 .5 divided by square root of 370 times of 147 .975.
02:04
On further calculating this, we get the correlation coefficient denoted by r is equal to negative 0 .5705.
02:13
Therefore, the correlation between the variables x and y is negative 0 .5705.
02:21
Now next we have the value of b1 is equal to, so we know sum of squares of xy divided by sum of squares of x, so this is equal to negative 133 .5 divided by 317...