Advertisements
Advertisements
प्रश्न
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
Advertisements
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
संबंधित प्रश्न
Bring out the inconsistency in the following:
bYX = bXY = 1.50 and r = - 0.9
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.
Estimate the likely sales for a proposed advertisement expenditure of ₹ 10 crores.
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?
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.
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.
Choose the correct alternative:
|byx + bxy| ≥ ______
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:
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:
The following data is not consistent: byx + bxy =1.3 and r = 0.75
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:
Corr(x, x) = 0
Corr(x, x) = 1
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 = ______
The value of product moment correlation coefficient between x and x is ______
The geometric mean of negative regression coefficients is ______
byx is the ______ of regression line of y on x
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?
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.
Mean of x = 53
Mean of y = 28
Regression coefficient of y on x = – 1.2
Regression coefficient of x on y = – 0.3
a. r = `square`
b. When x = 50,
`y - square = square (50 - square)`
∴ y = `square`
c. When y = 25,
`x - square = square (25 - square)`
∴ x = `square`
Mean of x = 25
Mean of y = 20
`sigma_x` = 4
`sigma_y` = 3
r = 0.5
byx = `square`
bxy = `square`
when x = 10,
`y - square = square (10 - square)`
∴ y = `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`
If byx > 1 then bxy is _______.
|bxy + byz| ≥ ______.
