Page 193 - DCOM203_DMGT204_QUANTITATIVE_TECHNIQUES_I
P. 193

Quantitative Techniques – I




                    Notes
                                                       x y
                                                        i i
                                   or            d       2                                  .... (18)
                                                        y
                                                         i
                                                    1
                                                         X i  X Y i  Y
                                                    n                  Cov X  ,Y
                                                       1         2         2                .... (19)
                                                            Y i  Y         Y
                                                       n
                                                     n  X Y      X     Y
                                                          i i     i    i
                                                 d
                                           Also              2       2                      .... (20)
                                                        n  Y i     Y i
                                   This  expression is useful for  calculating  the  value of  d. Another short-cut  formula for  the
                                   calculation of d is given by

                                                       n  u v     u     v
                                                     h     i i     i    i
                                                 d
                                                     k        2       2                     .... (21)
                                                          n  v i    v i
                                                    X - A         Y - B
                                          where u =  i     and v =  i
                                                               i
                                                 i
                                                      h             k
                                   Consider equation (19)
                                                    Cov X  ,Y  r  X Y    X
                                                 d                    r
                                                        2        2                          .... (22)
                                                        Y        Y       Y
                                   Substituting the value of c from equation (15) into line of regression of X on Y we have

                                                 X Ci  X dY dY or   X  Ci  X  d Y i  Y      .... (23)
                                                               i
                                          or  X  Ci  X  r  X  Y i  Y                        .... (24)
                                                          Y
                                   This shows that the line of regression also passes through the point  X,Y . Since both the lines
                                   of regression passes through the point  X,Y , therefore  X,Y  is their point of intersection as
                                   shown in Figure 9.3.
                                   9.1.3 Correlation Coefficient and the two Regression Coefficients



                                        b  r   Y      d   r   X
                                   Since          and             we have
                                               X              Y

                                    . b d  r  Y  r  X  r 2   or   r  . b d   This shows that correlation coefficient is the geometric
                                            X    Y
                                   mean of the two regression coefficients.

                                          Example: From the data given below, find:
                                   1.  The two regression equations.

                                   2.  The coefficient of correlation between marks in economics and statistics.





          188                               LOVELY PROFESSIONAL UNIVERSITY
   188   189   190   191   192   193   194   195   196   197   198