Archives

The coefficient of correlation for the following will be approximately

1) 0.90 2) 0.96 3) – 0.90 4) – 0.96 Solution: (2) 0.96 Here ∑x = 44, ∑y = 64 ∑x2 = 290, ∑y2 = 610 and ∑xy = 418 rxy = 0.96... View Article

The variables x and y represent height in cm and weight in gm respectively. The correlation between x and y has the unit

1) gm 2) cm 3) gm. cm 4) None of these Solution: (4) None of these Correlation is always unitless.... View Article

If the correlation between x and y is r, then between y and x correlation will be

1) –r 2) 1/r 3) r 4) 1– r Solution: (3) r If the correlation between x and y is r, then between y and x correlation will be r.... View Article

If r = – 0.97, then

1) Correlation is negative and curved 2) Correlation is linear and negative 3) Correlation is in the third and fourth quadrant 4) None of the... View Article

If r = 0.2, then the linear correlation will be necessarily

1) Perfect 2) Negative 3) Very low 4) Very high Solution: (3) Very low If r = 0.2, then the linear correlation will be necessarily very low.... View Article

The points of scatter diagram in perfect positive correlation are situated at the line

1) y = – x 2) y = x 3) y = 2x 4) y = – 2x Solution: (2) y = x The points of the scatter diagram in perfect positive correlation are situated... View Article

In a scatter diagram, the points are scattered equally in a corners of quadrants, then

1) r = 1 2) r = –1 3) r = 0 4) r = ± 1 / 2 Solution: (3) r = 0 The value of r is 0 when the points are scattered equally in the corners of... View Article

For the bivariate frequency table for x and y, then the marginal frequency distribution for y is given by

1) 0 - 10 6 10 - 20 11 20 - 30 14 30 - 40... View Article

If the variances of two variables x and y are respectively 9 and 16 and their covariance is 8, then their coefficient of correlation is

1) 2 / 3 2) 8 / 3 √2 3) 9 / 8 √2 4) 2 / 9 Solution: (1) 2 / 3 Coefficient of correlation r = cov (x, y) / [√var (x) . √var (y)] = 8 / (√9... View Article

Let x₁, x₂, x₃ ….. x_n be the ranks of n individuals according to character A and y₁, y₂ ….. y_n the ranks of the same individuals according to other character B such that x_i + y_i = n + 1 for i = 1, 2, 3 ….. N. Then the coefficient of rank correlation between the characters A and B is

1) 1 2) 0 3) –1 4) None of these Solution: (3) –1 xi + yi = n + 1 for all i = 1, 2, 3 …. N Let xi - yi = di, then 2xi = n + 1 + di di = 2xi... View Article

For the following pairs of observations (1, 10), (2, 9), (3, 9), (4, 8), (5, 6), (6, 12), (7, 4), (8, 3), (9, 13), (10, 1), then Cov (x, y) =

1) 1.05 2) 2.45 3) – 4.45 4) – 4.9 Solution: (3) – 4.45 Here x {bar} = 5.5, y {bar} = 7.5 x - {x bar} y - {y bar}... View Article

If var (x) = 21 / 4 and var (y) = 21 and r = 1, then standard error of y is

1) 0 2) 1/2 3) 1/4 4) 1 Solution: (1) 0 Sy = y √1 - r2 = y √1 - 1 = 0... View Article

The coefficients of correlation between the heights (in inches) of fathers and sons from the following data will be: Heights of fathers (x) 65 66 67 68 69 70 71. Heights of sons (y) 67 68 66 69 72 72 69

1) 0.60 2) – 0.60 3) – 0.67 4) 0.67 Solution: (4) 0.67 Mean of x = 68, Mean of y = 69 x - {x bar} y - {y bar} x -... View Article

Karl Pearson’s coefficient of rank correlation between the ranks obtained by ten students in Mathematics and Chemistry in a class test as given below is: Rank in Mathematics 1 2 3 4 5 6 7 8 9 10. Rank in Chemistry 3 10 5 1 2 9 4 8 7 6

1) 0.224 2) 0.204 3) 0.240 4) None of these Solution: (1) 0.224 Since, ∑d2 = 128 ⍴ = 1 - {[6 (128)] / [10 (100 - 1)]} = 0.224... View Article

If 2 random variables x and y of a bivariate distribution are connected by the relationship 3x + 2y = 4, then correlation coefficient r_xy =

1) 1 2) –1 3) 2/3 4) –2/3 Solution: (2) –1 Here, y = (- 3 / 2) x + 2 Since x and y are related linearly and the slope of the relation is... View Article

For the given data, the calculation corresponding to all value of pairs (x, y) is following ∑ (x – x {bar})² = 36, ∑ (x – y {bar})² = 25, ∑ (x – x {bar}) ∑ (y – y {bar}) = 2. Then the Karl Pearson’s correlation coefficient is

1) 0.2 2) 0.5 3) 0.66 4) 0.33 Solution: (3) 0.66 rxy = 20 / √(36) (25) = 2 / 3 = 0.66... View Article