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प्रश्न
For a certain bivariate data of a group of 10 students, the following information gives the internal marks obtained in English (X) and Hindi (Y):
| X | Y | |
| Mean | 13 | 17 |
| Standard Deviation | 3 | 2 |
If r = 0.6, Estimate x when y = 16 and y when x = 10
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उत्तर
Given, `barx` = 13, `bary` = 17, `sigma_x` = 3, `sigma_y` = 2, r = 0.6
byx = `"r" sigma_y/sigma_x = 0.6 xx 2/3` = 0.4
bxy = `"r" sigma_x/sigma_y = 0.6 xx 3/2` = 0.9
The regression equation of X on Y is given by `("X" - barx) = "b"_(xy) ("Y" - bary)`
(X – 13) = 0.9(Y – 17)
X – 13 = 0.9Y – 15.3
X = 0.9Y – 15.3 + 13
X = – 2.3 + 0.9Y ......(i)
For Y = 16, from equation (i) we get
X = – 2.3 + (0.9)(16)
= – 2.3 + 14.4
= 12.1
The regression equation of Y on X is given by `("Y" - bary) = "b"_(yx) ("X" - barx)`
(Y – 17) = 0.4(X – 13)
Y – 17 = 0.4X – 5.2
Y = 0.4X – 5.2 + 17
Y = 11.8 + 0.4X .....(ii)
For X = 10, from equation (ii) we get
Y = 11.8 + 0.4(10)
= 11.8 + 4
= 15.8
संबंधित प्रश्न
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| Advertisement expenditure (₹ in lakh) (X) |
Sales (₹ in lakh) (Y) | |
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| Standard Mean | 3 | 12 |
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Bring out the inconsistency in the following:
bYX = 2.6 and bXY = `1/2.6`
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| X | Y | |
| Mean | 25 | 20 |
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| X | Y | |
| Mean | 50 | 140 |
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Choose the correct alternative:
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Choose the correct alternative:
If r = 0.5, σx = 3, σy2 = 16, then bxy = ______
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If n = 5, ∑xy = 76, ∑x2 = ∑y2 = 90, ∑x = 20 = ∑y, the covariance = ______
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Obtain the two regression lines:
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DEMAND (y) (₹ in lakhs) |
|
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| Variance | 9 | 144 |
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If n = 5, Σx = Σy = 20, Σx2 = Σy2 = 90 , Σxy = 76 Find Covariance (x,y)
| 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`
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`
