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The two regression lines between height (X) in inches and weight (Y) in kgs of girls are, 4y − 15x + 500 = 0 and 20x − 3y − 900 = 0

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प्रश्न

The two regression lines between height (X) in inches and weight (Y) in kgs of girls are,
4y − 15x + 500 = 0
and 20x − 3y − 900 = 0
Find the mean height and weight of the group. Also, estimate the weight of a girl whose height is 70 inches.

योग
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उत्तर

Given, X = Height (in inches), Y = weight (in Kg)

The equation of regression are

4y - 15x + 500 = 0

i.e., –15x + 4y = – 500     …(i)

and 20x – 3y – 900 = 0

i.e., 20x – 3y = 900        …(ii)

By 3 × (i) + 4 × (ii), we get

- 45x + 12y = - 1500
+ 80x - 12y = 3600   
35x  =  2100
∴ x = 60

Substituting x = 60 in (i), we get

–15(60) + 4y = –500

∴ 4y = 900 – 500

∴ y = 100

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

`bar x` = mean height of the group = 60 inches, and 
`bar y` = mean weight of the group = 100 kg.

Let 4y – 15x + 500 = 0 be the regression equation of Y on X.

∴ The equation becomes 4y = 15x – 500

i.e., Y = `15/4"X" - 500/4`    ...(i)

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

∴ `"b"_"YX" = 15/4`

∴ Now, other equation 20x – 3y – 900 = 0 be the regression equation of X on Y

∴The equation becomes 20x – 3y – 900 = 0

i.e., 20x = 3y + 900

X = `3/20"Y" + 900/20`

Comparing it with X = bXY Y + a',

∴ `"b"_"XY" = 3/20`

Now, `"b"_"YX" * "b"_"XY" = 15/4 * 3/20 = 0.5625`

i.e., bXY . bYX < 1

∴ Assumption of regression equations is true.

Now, substituting x = 70 in (i) we get

y = `15/4 xx 70 - 500/4 = (1050 - 500)/4 = 550/4 = 137.5`

∴ Weight of girl having height 70 inches is 137.5 kg

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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 ५०]

APPEARS IN

बालभारती Mathematics and Statistics 2 (Commerce) [English] Standard 12 Maharashtra State Board
अध्याय 3 Linear Regression
Exercise 3.3 | Q 14 | पृष्ठ ५०

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.


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.
  2. The line regression of X on Y.
  3. The correlation coefficient between X and Y.

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`


For certain bivariate data the following information is available.

  X Y
Mean 13 17
S.D. 3 2

Correlation coefficient between x and y is 0.6. estimate x when y = 15 and estimate y when x = 10.


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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For 50 students of a class, the regression equation of marks in statistics (X) on the marks in accountancy (Y) is 3y − 5x + 180 = 0.  The variance of marks in statistics is `(9/16)^"th"` of the variance of marks in accountancy. Find the correlation coefficient between marks in two subjects.


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.


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"`

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


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.


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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`


State whether the following statement is True or False: 

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 


|bxy + byx| ≥ ______


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 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


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


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`


x y xy x2 y2
6 9 54 36 81
2 11 22 4 121
10 5 50 100 25
4 8 32 16 64
8 7 `square` 64 49
Total = 30 Total = 40 Total = `square` Total = 220 Total = `square`

bxy = `square/square`

byx = `square/square`

∴ Regression equation of x on y is `square`

∴ Regression equation of y on x is `square`


|bxy + byz| ≥ ______.


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