 Welcome to the session. In this session, we will discuss a question which says that, how do the regression coefficients dyx and dxy for the following data also find the correlation coefficient? And in this data, it is given n is equal to 5, summation x is equal to 15, summation x square is equal to 55, summation y is equal to 25, summation y square is equal to 151, and summation xy is equal to 88. Now, before starting the solution of this question, we should do some results. And therefore, the regression coefficient of y on x, that is, dyx dyx is given by the formula summation xy minus summation x into summation y over n over x square minus summation x square by n. And secondly, the regression coefficient of x and y, that is, dxy is given by the formula summation xy minus summation x into summation y over n over n, summation y square minus summation y whole square by n to coefficient. And the value apart varies from minus 1, which will work out as a key idea. And now, we will start with the solution. Using this data, we have to find the regression coefficient to coefficient. Subdivine x is equal to 15, summation x square is equal to 55, summation y is equal to 25, summation y square is equal to 151, is equal to 88, which are given in the key idea. Now, the regression coefficient of y on x dyx is given by the formula summation xy minus summation x into summation y over n minus summation x whole square by summation y is 25, summation x square is 55 and summation xy is 88 and n is... So, using all these values here, this is equal to 28 minus minus 15 square minus 375. I am solving this is equal to... Now, 450 minus 375 is 65 over... Equal to 65.50. And I am solving it again, 1.3, 0.5 to 1.3. It is given by the formula summation xy minus summation x into summation y. This summation y whole square, summation y square is 151 and minus 15 into 25 by 5 is 25. So, this is equal to 0.5. Therefore, n is equal to 0.5. Now, b y is 1.3 and b y is 0.2 is equal to 1.3 into 0.5, which further gives r square is equal to 0.65, which implies r is equal to plus minus 0.8062. Now, view of b y x and b x y, that is, if b x y and b y x both are positive, then r is also positive while both are negative, then r is also negative. Therefore, r is equal to 0.8062. The regression coefficient b y x is equal to 1.3. The regression coefficient b y x y is equal to 0.5. The coefficient is equal to 0.80 of the given question. And that's all for this session. Hope you all have enjoyed the session.