The Karl Pearson's coefficient of correlation
Cannot be greater than-1
Lies in the closed interval [-1,1]
lies in the open interval (-1,1)
None of these.
If cov(x,y)= -1.55, var (x) = 1.55, var (y)= 1.55, then ρ(x,y) =
1
-1
0
In the case of perfect correlation between x and y, the number of regression lines is
2
More than 2
The regression coefficients are -0.8 and -0.8. The coefficient of correlation is
0.64
0.8
-0.8
If bxy is positive then byx is
Positive
Negative
Can be any
If the two regression lines are x+4y=3 and 3x+y =15, then the value of x for which y = 5 is
3/10
-17
10/3
1/17
The lines of regressions make angles 300 and 600 with the positive direction of the x-axis . Then the coefficient of correlation between x and y is
√3
1/√3
The regression lines are x =0.49 y and y = 0.81 x . The coefficient of correlation is
6.3
0.63
63
The square of the correlation coefficient is
The square of the regression coefficient
The square root of the regression coefficient
The product of the regression coefficient
Always unity.
Two regression lines are given by 4x+3y+7 = 0 and 3x+4y+8 = 0. Then the regression line of y on x is
4x+3y+7= 0
3x+4y+8 = 0
Neither is the regression lines of y on x
