हिंदी

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

Advertisements
Advertisements

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
Advertisements

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

shaalaa.com
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

You are given the following information about advertising expenditure and sales.

  Advertisement expenditure
(₹ in lakh) (X)
Sales (₹ in lakh) (Y)
Arithmetic Mean 10 90
Standard Mean 3 12

Correlation coefficient between X and Y is 0.8

  1. Obtain the two regression equations.
  2. What is the likely sales when the advertising budget is ₹ 15 lakh?
  3. What should be the advertising budget if the company wants to attain sales target of ₹ 120 lakh?

Bring out the inconsistency in the following:

bYX = 1.9 and bXY = - 0.25


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.


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?


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 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.


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

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


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


State whether the following statement is True or False:

The following data is not consistent: byx + bxy =1.3 and r = 0.75


Corr(x, x) = 1


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


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


Arithmetic mean of positive values of regression coefficients is greater than or equal to ______


byx 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.


If n = 5, Σx = Σy = 20, Σx2 = Σy2 = 90 , Σxy = 76 Find Covariance (x,y) 


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`


If byx > 1 then bxy is _______.


The following results were obtained from records of age (x) and systolic blood pressure (y) of a group of 10 women.

  x y
Mean 53 142
Variance 130 165

`sum(x_i - barx)(y_i - bary)` = 1170


For a bivariate data:

`sum(x - overlinex)^2` = 1200, `sum(y - overliney)^2` = 300, `sum(x - overlinex)(y - overliney)` = – 250

Find: 

  1. byx
  2. bxy
  3. Correlation coefficient between x and y.

Share
Notifications

Englishहिंदीमराठी


      Forgot password?
Use app×