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Given the following information about the production and demand of a commodity obtain the two regression lines: Coefficient of correlation between X and Y is 0.6. - Mathematics and Statistics

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Question

Given the following information about the production and demand of a commodity obtain the two regression lines:

  X Y
Mean 85 90
S.D. 5 6

The coefficient of correlation between X and Y is 0.6. Also estimate the production when demand is 100.

Sum

Solution

Given, `bar x = 85, bar y = 90, sigma_"X" = 5, sigma_"Y" = 6`, r =0.6

`"b"_"YX" = "r" sigma_"Y"/sigma_"X" = 0.6 xx 6/5 = 0.72`

`"b"_"XY" = "r" sigma_"X"/sigma_"Y" = 0.6 xx 5/6 = 0.5`

The regression equation of Y on X is

`("Y" - bar y) = "b"_"YX" ("X" - bar x)`

(Y - 90) = 0.72 (X - 85)

Y - 90 = 0.72 X - 61.2

Y = 0.72X - 61.2 + 90

Y = 28.8 + 0.72 X           ....(i)

The regression equation of X on Y is

`("X" - bar x) = "b"_"XY" ("Y" - bar y)`

(X - 85) = 0.5(Y - 90)

X - 85 = 0.5 Y - 45

X = 0.5 Y - 45 + 85

X = 40 + 0.5Y            ....(ii)

For Y = 100, from equation (ii) we get

X = 40 + 0.5(100) = 40 + 50 = 90

∴ The production is 90 when demand is 100.

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Notes

The answer in the textbook is incorrect.

Properties of Regression Coefficients
  Is there an error in this question or solution?
Chapter 3: Linear Regression - Exercise 3.2 [Page 48]

RELATED QUESTIONS

From the data of 7 pairs of observations on X and Y, following results are obtained.

∑(xi - 70) = - 35,  ∑(yi - 60) = - 7,

∑(xi - 70)2 = 2989,    ∑(yi - 60)2 = 476, 

∑(xi - 70)(yi - 60) = 1064

[Given: `sqrt0.7884` = 0.8879]

Obtain

  1. The line of regression of Y on X.
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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

  1. The mean values of X and Y.
  2. Correlation coefficient between X and Y.
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In a partially destroyed record, the following data are available: variance of X = 25, Regression equation of Y on X is 5y − x = 22 and regression equation of X on Y is 64x − 45y = 22 Find

  1. Mean values of X and Y
  2. Standard deviation of Y
  3. Coefficient of correlation between X and Y.

The two regression equations are 5x − 6y + 90 = 0 and 15x − 8y − 130 = 0. Find `bar x, bar y`, r.


The equations of two regression lines are 10x − 4y = 80 and 10y − 9x = − 40 Find:

  1. `bar x and bar y`
  2. bYX and bXY
  3. If var (Y) = 36, obtain var (X)
  4. r

Choose the correct alternative:

If for a bivariate data, bYX = – 1.2 and bXY = – 0.3, then r = ______


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 σx = 2, σy = 8


Choose the correct alternative:

Both the regression coefficients cannot exceed 1


State whether the following statement is True or False: 

If u = x – a and v = y – b then bxy = buv 


State whether the following statement is True or False:

Corr(x, x) = 0


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


|bxy + byx| ≥ ______


If the sign of the correlation coefficient is negative, then the sign of the slope of the respective regression line is ______


If u = `(x - 20)/5` and v = `(y - 30)/4`, then byx = ______


The equations of two lines of regression are 3x + 2y – 26 = 0 and 6x + y – 31 = 0. Find variance of x if variance of y is 36


For a certain bivariate data of a group of 10 students, the following information gives the internal marks obtained in English (X) and Hindi (Y):

  X Y
Mean 13 17
Standard Deviation 3 2

If r = 0.6, Estimate x when y = 16 and y when x = 10


x y `x - barx` `y - bary` `(x - barx)(y - bary)` `(x - barx)^2` `(y - bary)^2`
1 5 – 2 – 4 8 4 16
2 7 – 1 – 2 `square` 1 4
3 9 0 0 0 0 0
4 11 1 2 2 4 4
5 13 2 4 8 1 16
Total = 15 Total = 45 Total = 0 Total = 0 Total = `square` Total = 10 Total = 40

Mean of x = `barx = square`

Mean of y = `bary = square`

bxy = `square/square`

byx = `square/square`

Regression equation of x on y is `(x - barx) = "b"_(xy)  (y - bary)`

∴ Regression equation x on y is `square`

Regression equation of y on x is `(y - bary) = "b"_(yx)  (x - barx)`

∴ Regression equation of y on x is `square`


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`


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