00:01
Hello students, for the given data, the calculation table is as follows.
00:11
Now, party correlation between x and y, that is, correlation of x, y is equal to r, that is equal to n into summation xy minus summation x into summation y divided by square root of n into summation x square minus summation x whole square into n into summation y square minus summation y whole square.
00:57
Now, here n is equal to 5, then this is equal to 5 into summation xy value, that is, this one 8100 minus 58 into 650, so this is all the totals of the values divided by square root of 5 into 714 minus 58 square into 5 into 650, 93300 minus 650 square.
01:43
So, solving we get r is equal to 0 .93.
01:55
Now, for the part b, we know that summation x is equal to 58, summation x square is equal to 714, summation y is equal to 650, summation xy is equal to 8100, n is equal to 5.
02:14
Then, slope of the regression line, that is, b is equal to n into summation xy minus summation x into summation y divided by n into summation x square minus summation x whole square.
02:39
So, that is equal to 5 into 8100 minus 58 into 650 divided by 5 into 714 minus 58 square, that is equal to 13 .5922, that is, slope b.
02:57
Now, y intercept of regression line, that is, a is equal to summation y minus b into summation x divided by n, that is equal to 650 minus 13 .5922 into 58 divided by 5, which is equivalent to minus 27 .6699.
03:29
Therefore, linear regression model y cap is equal to bx plus e, that is equal to 13 .5922 into x minus 27 .6699.
03:57
Now, interpretation is as follows.
04:03
For a unit million increase in advertising, we expect an increase of 13 .5922 million in total profit of an average...