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प्रश्न
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?
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उत्तर
Given, `bar(x)` = 10, `bar(y)` = 90, `sigma_x^2` = 9, `sigma_y^2` = 144, r = 0.8
∴ `sigma_x` = 3, `sigma_y` = 12
byx = `"r" sigma_y/sigma_x = 0.8 xx 12/3` = 0.8 × 4 = 3.2
bxy = `"r" sigma_x/sigma_y = 0.8 xx 3/12` = 0.8 × 0.25 = 0.2
The regression equation of Y on X is
`("Y" - bary) = "b"_(yx) ("X" - barx)`
∴ (Y – 90) = 3.2 (X – 10)
∴ Y – 90 = 3.2 X – 32
∴ Y = 3.2 X – 32 + 90
∴ Y = 3.2 X + 58 ......(i)
The regression equation of X on Y is
`("X" - barx) = "b"_(xy) ("Y" - bary)`
∴ (X – 10) = 0.2 (Y – 90)
∴ X – 10 = 0.2 Y – 18
∴ X = 0.2 Y – 18 + 10
∴ X = 0.2 Y – 8 ......(ii)
When the company wants to attain the sales target of ₹ 150 lakhs,
Put Y = 150 lakh in equation (ii)
∴ X = 0.2 × 150 – 8 = 30 – 8 = 22
∴ The advertising budget should be ₹ 22 lakhs if the company wants to attain the sales target of ₹ 150 lakhs.
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
- The line of regression of Y on X.
- The line regression of X on Y.
- The correlation coefficient between X and Y.
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
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- What is the likely sales when the advertising budget is ₹ 15 lakh?
- 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 + bXY = 1.30 and r = 0.75
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bYX = 1.9 and bXY = - 0.25
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Variance of X = 9
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8x − 10y + 66 = 0
and 40x − 18y = 214.
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- Correlation coefficient between X and Y.
- Standard deviation of Y.
For a bivariate data, `bar x = 53`, `bar y = 28`, byx = −1.5 and bxy = −0.2. Estimate y when x = 50.
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
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- Coefficient of correlation 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
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- r [Given `sqrt0.375` = 0.61]
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.
If bYX = − 0.6 and bXY = − 0.216, then find correlation coefficient between X and Y. Comment on it.
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If byx < 0 and bxy < 0, then r is ______
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, σy2 = 16, then bxy = ______
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:
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:
Cov(x, x) = Variance of x
If n = 5, ∑xy = 76, ∑x2 = ∑y2 = 90, ∑x = 20 = ∑y, the covariance = ______
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
Mean of x = 25
Mean of y = 20
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bxy = `square`
when x = 10,
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The regression equation of y on x is 2x – 5y + 60 = 0
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∴ byx = `square/square`
∴ r = `square`
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
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