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If n = 5, ∑xy = 76, ∑x^{2} = ∑y^{2} = 90, ∑x = 20 = ∑y, the covariance = ______
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Solution
– 0.8
RELATED QUESTIONS
For bivariate data. `bar x = 53, bar y = 28, "b"_"YX" =  1.2, "b"_"XY" =  0.3` Find estimate of Y for X = 50.
For bivariate data. `bar x = 53, bar y = 28, "b"_"YX" =  1.2, "b"_"XY" =  0.3` Find estimate of X for Y = 25.
From the data of 7 pairs of observations on X and Y, following results are obtained.
∑(x_{i}  70) =  35, ∑(y_{i}  60) =  7,
∑(x_{i}  70)^{2} = 2989, ∑(y_{i}  60)^{2} = 476,
∑(x_{i}  70)(y_{i}  60) = 1064
[Given: `sqrt0.7884` = 0.8879]
Obtain
 The line of regression of Y on X.
 The line regression of X on Y.
 The correlation coefficient between X and Y.
Bring out the inconsistency in the following:
b_{YX} = 2.6 and b_{XY} = `1/2.6`
The following data about the sales and advertisement expenditure of a firms is given below (in ₹ Crores)
Sales  Adv. Exp.  
Mean  40  6 
S.D.  10  1.5 
Coefficient of correlation between sales and advertisement expenditure is 0.9.
Estimate the likely sales for a proposed advertisement expenditure of ₹ 10 crores.
In a partially destroyed laboratory record of an analysis of regression data, the following data are legible:
Variance of X = 9
Regression equations:
8x − 10y + 66 = 0
and 40x − 18y = 214.
Find on the basis of above information
 The mean values of X and Y.
 Correlation coefficient between X and Y.
 Standard deviation of Y.
The equations of two regression lines are x − 4y = 5 and 16y − x = 64. Find means of X and Y. Also, find correlation coefficient between X and Y.
If the two regression lines for a bivariate data are 2x = y + 15 (x on y) and 4y = 3x + 25 (y on x), find
 `bar x`,
 `bar y`,
 b_{YX}
 b_{XY}
 r [Given `sqrt0.375` = 0.61]
Regression equations of two series are 2x − y − 15 = 0 and 3x − 4y + 25 = 0. Find `bar x, bar y` and regression coefficients. Also find coefficients of correlation. [Given `sqrt0.375` = 0.61]
Find the line of regression of X on Y for the following data:
n = 8, `sum(x_i  bar x)^2 = 36, sum(y_i  bar y)^2 = 44, sum(x_i  bar x)(y_i  bar y) = 24`
The equations of two regression lines are 10x − 4y = 80 and 10y − 9x = − 40 Find:
 `bar x and bar y`
 `"b"_"YX" and "b"_"XY"`
 If var (Y) = 36, obtain var (X)
 r
Choose the correct alternative:
If b_{yx} < 0 and b_{xy} < 0, then r is ______
Choose the correct alternative:
Find the value of the covariance between X and Y, if the regression coefficient of Y on X is 3.75 and σ_{x} = 2, σ_{y} = 8
Choose the correct alternative:
If r = 0.5, σ_{x} = 3, `σ_"y"^2` = 16, then b_{yx} = ______
Choose the correct alternative:
Both the regression coefficients cannot exceed 1
State whether the following statement is True or False:
The following data is not consistent: b_{yx} + b_{xy} =1.3 and r = 0.75
State whether the following statement is True or False:
Corr(x, x) = 0
State whether the following statement is True or False:
Cov(x, x) = Variance of x
State whether the following statement is True or False:
Regression coefficient of x on y is the slope of regression line of x on y
b_{xy} + b_{yx} ≥ ______
The geometric mean of negative regression coefficients is ______
b_{yx} is the ______ of regression line of y on x
The equations of the two lines of regression are 2x + 3y − 6 = 0 and 5x + 7y − 12 = 0. Find the value of the correlation coefficient `("Given" sqrt(0.933) = 0.9667)`
Given the following information about the production and demand of a commodity.
Obtain the two regression lines:
Production (X) 
Demand (Y) 

Mean  85  90 
Variance  25  36 
Coefficient of correlation between X and Y is 0.6. Also estimate the demand when the production is 100 units.
The equations of the two lines of regression are 6x + y − 31 = 0 and 3x + 2y – 26 = 0. Find the value of the correlation coefficient
Mean of x = 53
Mean of y = 28
Regression coefficient of y on x = – 1.2
Regression coefficient of x on y = – 0.3
a. r = `square`
b. When x = 50,
`y  square = square (50  square)`
∴ y = `square`
c. When y = 25,
`x  square = square (25  square)`
∴ x = `square`
Mean of x = 25
Mean of y = 20
`sigma_x` = 4
`sigma_y` = 3
r = 0.5
b_{yx} = `square`
b_{xy} = `square`
when x = 10,
`y  square = square (10  square)`
∴ y = `square`
The regression equation of y on x is 2x – 5y + 60 = 0
Mean of x = 18
`2 square  5 bary + 60` = 0
∴ `bary = square`
`sigma_x : sigma_y` = 3 : 2
∴ b_{yx} = `square/square`
∴ b_{yx} = `square/square`
∴ r = `square`
If b_{yx} > 1 then b_{xy} is _______.