Advertisements
Advertisements
प्रश्न
For a bivariate data:
`sum(x - overlinex)^2` = 1200, `sum(y - overliney)^2` = 300, `sum(x - overlinex)(y - overliney)` = – 250
Find:
- byx
- bxy
- Correlation coefficient between x and y.
उत्तर
`sum(x - overlinex)^2` = 1200, `sum(y - overliney)^2` = 300
`sum(x - overlinex)(y - overliney)` = – 250
cov (x, y) = `(sum(x - overlinex).(y - overliney))/n`
= `(-250)/n`
(σx)2 = `sqrt((sum(x - overlinex)^2)/n`
= `sqrt(1200/n)`
= `1200/n`
(σy)2 = `sqrt((sum(y - overliney)^2)/n`
= `sqrt(300/n)`
= `300/n`
byx = `(cov (x, y))/(σ_x)^2`
= `((-250)/n)/(1200/n)`
= `(-5)/60`
byx = `(-1)/12`
bxy = `(cov (x, y))/(σ_y)^2`
= `((-250)/n)/(300/n)`
bxy = `(-5)/6`
r = `±sqrt(b_(yx) . b_(xy))`
= `-sqrt((-1)/12 xx (-5)/6)`
= `-sqrt(5/72)`
= `-sqrt(0.07)`
APPEARS IN
संबंधित प्रश्न
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
- The line of regression of Y on X.
- The line regression of X on Y.
- The correlation coefficient between X and Y.
Bring out the inconsistency in the following:
bYX = 1.9 and bXY = - 0.25
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?
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.
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.
The equations of two regression lines are
2x + 3y − 6 = 0
and 3x + 2y − 12 = 0 Find
- Correlation coefficient
- `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 equations of two regression lines are x − 4y = 5 and 16y − x = 64. Find means of X and Y. Also, find correlation coefficient between X and Y.
If the two regression lines for a bivariate data are 2x = y + 15 (x on y) and 4y = 3x + 25 (y on x), find
- `bar x`,
- `bar y`,
- bYX
- bXY
- r [Given `sqrt0.375` = 0.61]
The two regression equations are 5x − 6y + 90 = 0 and 15x − 8y − 130 = 0. Find `bar x, bar y`, r.
Regression equations of two series are 2x − y − 15 = 0 and 3x − 4y + 25 = 0. Find `bar x, bar y` and regression coefficients. Also find coefficients of correlation. [Given `sqrt0.375` = 0.61]
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.
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`
The equations of two regression lines are 10x − 4y = 80 and 10y − 9x = − 40 Find:
- `bar x and bar y`
- bYX and bXY
- If var (Y) = 36, obtain var (X)
- r
If bYX = − 0.6 and bXY = − 0.216, then find correlation coefficient between X and Y. Comment on it.
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:
bxy and byx are ______
Choose the correct alternative:
Both the regression coefficients cannot exceed 1
The following data is not consistent: byx + bxy =1.3 and r = 0.75
Corr(x, x) = 1
Given the following information about the production and demand of a commodity.
Obtain the two regression lines:
ADVERTISEMENT (x) (₹ in lakhs) |
DEMAND (y) (₹ in lakhs) |
|
Mean | 10 | 90 |
Variance | 9 | 144 |
Coefficient of correlation between x and y is 0.8.
What should be the advertising budget if the company wants to attain the sales target of ₹ 150 lakhs?
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`
bxy . byx = ______.
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