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महाराष्ट्र राज्य शिक्षण मंडळएचएससी वाणिज्य (इंग्रजी माध्यम) इयत्ता १२ वी

The equations of two regression lines are 10x − 4y = 80 and 10y − 9x = − 40 Find: andx¯andy¯ bYXandbXYbYXandbXY If var (Y) = 36, obtain var (X) r - Mathematics and Statistics

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प्रश्न

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
बेरीज
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उत्तर

(i) Given equations of regression are

10x − 4y = 80

i.e., 5x − 2y = 40        .....(i)

and 10y − 9x = −40

i.e., − 9x + 10y = −40         .....(ii)

By 5 × (i) + (ii), we get

 25x − 10y = 200

− 9x + 10y = − 40 
16x             = 160

∴ x = 10

Substituting x = 10 in (i), we get

5(10) − 2y = 40

∴ 50 − 2y = 40

∴ −2y = 40 − 50

∴ −2y = − 10

∴ y = 5

Since the point of intersection of two regression lines is `(bar x, bar y)`, `bar x = 10  and bar y = 5`

(ii) Let 10y − 9x = −40 be the regression equation of Y on X.

∴ The equation becomes 10Y = 9X − 40

i.e., Y = `9/10X − 40/10`

Comparing it with Y = bYX X + a, we get

`b_(YX) = 9/10 = 0.9`

Now, the other equation 10x − 4y = 80 be the regression equation of X on Y.

∴ The equation becomes 10X = 4Y + 80

i.e., X = `4/10 Y + 80/10`

i.e., X = `2/5 Y + 8`

Comparing it with X = bXY Y + a', we get

`b_(XY) = 2/5 = 0.4`

(iii) Given, Var (Y) = 36, i.e., `sigma_Y^2` = 36

∴ σY = 6

Since `b_(XY) = r xx sigma_X/sigma_Y`

`2/5 = 0.6 xx sigma_X/6`

∴ `2/5 = 0.1 xx sigma_X`

∴ `2/(5 xx 0.1) = sigma_X`

∴ `sigma_X` = 4

∴ `sigma_X^2 = 16` i.e., Var(X) = 16

(iv) r = `+-sqrt(b_(XY) *b_(YX)`

`= +-sqrt(2/5 xx 9/10) +- sqrt(9/25)`

`= +- 3/5`

 `= +- 0.6`

Since bYX and bXY are positive,

r is also positive.

∴ r = 0.6

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Properties of Regression Coefficients
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पाठ 3: Linear Regression - Miscellaneous Exercise 3 [पृष्ठ ५४]

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बालभारती Mathematics and Statistics 2 (Commerce) [English] Standard 12 Maharashtra State Board
पाठ 3 Linear Regression
Miscellaneous Exercise 3 | Q 4.11 | पृष्ठ ५४

संबंधित प्रश्‍न

For bivariate data. `bar x = 53, bar y = 28, "b"_"YX" = - 1.2, "b"_"XY" = - 0.3` Find estimate of Y for X = 50.


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For a certain bivariate data

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Mean 25 20
S.D. 4 3

And r = 0.5. Estimate y when x = 10 and estimate x when y = 16


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  X Y
Mean 85 90
S.D. 5 6

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An inquiry of 50 families to study the relationship between expenditure on accommodation (₹ x) and expenditure on food and entertainment (₹ y) gave the following results: 

∑ x = 8500, ∑ y = 9600, σX = 60, σY = 20, r = 0.6

Estimate the expenditure on food and entertainment when expenditure on accommodation is Rs 200.


The following data about the sales and advertisement expenditure of a firms is given below (in ₹ Crores)

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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
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8x − 10y + 66 = 0
and 40x − 18y = 214.
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For bivariate data, the regression coefficient of Y on X is 0.4 and the regression coefficient of X on Y is 0.9. Find the value of the variance of Y if the variance of X is 9.


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Two lines of regression are 10x + 3y − 62 = 0 and 6x + 5y − 50 = 0. Identify the regression of x on y. Hence find `bar x, bar y` and r.


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`


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  X Y
Mean 50 140
Variance 150 165

and `sum (x_i - bar x)(y_i - bar y) = 1120`. Find the prediction of blood pressure of a man of age 40 years.


If bYX = − 0.6 and bXY = − 0.216, then find correlation coefficient between X and Y. Comment on it.


Choose the correct alternative:

If byx < 0 and bxy < 0, then r is ______


Choose the correct alternative:

Both the regression coefficients cannot exceed 1


State whether the following statement is True or False:

If byx = 1.5 and bxy = `1/3` then r = `1/2`, the given data is consistent


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If bxy < 0 and byx < 0 then ‘r’ is > 0


State whether the following statement is True or False: 

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


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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

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Mean of y = `bary = square`

bxy = `square/square`

byx = `square/square`

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  x y
Mean 53 142
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`sum(x_i - barx)(y_i - bary)` = 1170


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