हिंदी

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.

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प्रश्न

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.
  3. Standard deviation of Y.
योग
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उत्तर

Given, `sigma_"X"^2 = 9`

∴ σX = 3

(i) The two regression equations are

8x - 10y + 66 = 0

i.e., 8x - 10y = - 66      ...(i)

and 40x - 18y = 214    ....(ii)

By 5 × (i) - (ii), we get

40x - 50y = - 330

40x - 18y = 214
(-)    (+)      (-)   
- 32y = - 544

∴ y = `544/32 = 17`

Substituting y = 17 in (i), we get

8x - 10 × 17 = - 66

∴ 8x - 170 = - 66

∴ 8x = - 66 + 170

∴ 8x = 104

∴ x = `104/8 = 13`

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

`bar x` = mean value of X = 13, and

`bar y` = mean value of X = 17.

(ii) Let 8x - 10y + 66 = 0 be the regression equation of Y on X.

∴ The equation becomes 10Y = 8X + 66

i.e., Y = `8/10 "X" + 66/10`

i.e., Y = `4/5 "X" + 33/5`

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

`"b"_"YX" = 4/5`

Now, the other equation, i.e., 40x - 18y = 214 is the regression equation of X on Y.

∴ The equation becomes X = `18/40 "Y" + 214/40`

i.e., X = `9/20 "Y" + 107/20`

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

`"b"_"XY" = 9/20`

r = `+- sqrt("b"_"XY" * "b"_"YX")`

∴ r = `+- sqrt(9/20 xx 4/5) = +- sqrt(9/25) = +- 3/5 = +- 0.6`

Since bYX and bXY both are positive,

r is also positive.

∴ r = 0.6

(iii) `"b"_"YX" = "r" sigma_"Y"/sigma_"X"`

∴ `4/5 = 0.6 xx sigma_"Y"/3`

∴ `4/5 = sigma_"Y"/5`

∴ `sigma_"Y" = 4`

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Properties of Regression Coefficients
  क्या इस प्रश्न या उत्तर में कोई त्रुटि है?
अध्याय 3: Linear Regression - Exercise 3.3 [पृष्ठ ४९]

APPEARS IN

बालभारती Mathematics and Statistics 2 (Commerce) [English] Standard 12 Maharashtra State Board
अध्याय 3 Linear Regression
Exercise 3.3 | Q 2 | पृष्ठ ४९

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.


Bring out the inconsistency in the following:

bYX = 1.9 and bXY = - 0.25


Bring out the inconsistency in the following:

bYX = 2.6 and bXY = `1/2.6`


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.


Two samples from bivariate populations have 15 observations each. The sample means of X and Y are 25 and 18 respectively. The corresponding sum of squares of deviations from respective means is 136 and 150. The sum of the product of deviations from respective means is 123. Obtain the equation of the line of regression of X on Y.


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)

  Sales Adv. Exp.
Mean 40 6
S.D. 10 1.5

Coefficient of correlation between sales and advertisement expenditure is 0.9.

What should be the advertisement expenditure if the firm proposes a sales target ₹ 60 crores?


From the two regression equations, find r, `bar x and bar y`. 4y = 9x + 15 and 25x = 4y + 17


The equations of two regression lines are
2x + 3y − 6 = 0
and 3x + 2y − 12 = 0 Find 

  1. Correlation coefficient
  2. `sigma_"X"/sigma_"Y"`

For a bivariate data, `bar x = 53`, `bar y = 28`, byx = −1.5 and bxy = −0.2. Estimate y when x = 50.


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


The following results were obtained from records of age (X) and systolic blood pressure (Y) of a group of 10 men.

  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.


Choose the correct alternative:

|byx + bxy| ≥ ______


Choose the correct alternative:

If r = 0.5, σx = 3, `σ_"y"^2` = 16, then byx = ______


Choose the correct alternative:

If r = 0.5, σx = 3, σy2 = 16, then bxy = ______


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:

Cov(x, x) = Variance of x


If n = 5, ∑xy = 76, ∑x2 = ∑y2 = 90, ∑x = 20 = ∑y, the covariance = ______


If u = `(x - "a")/"c"` and v = `(y - "b")/"d"`, then bxy = ______ 


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


The geometric mean of negative regression coefficients is ______


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


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.


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`


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

∴ byx = `square/square`

∴ byx = `square/square`

∴ r = `square`


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