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Questions
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 byx + bxy = 1.3 and r = 0.75 then the given data is inconsistent.
Options
True
False
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Solution
This statement is true.
Explanation:
The given data is inconsistent because the equation byx + bxy = 1 + r2 should hold. Here 1 + (0.75)2 = 1.5626, but the given sum is 1.3, which contradicts the formula.
RELATED QUESTIONS
For bivariate data. `bar x = 53`, `bar y = 28`, byx = −1.2, bxy = −0.3. Find the correlation coefficient between x and y.
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For certain bivariate data the following information is available.
| X | Y | |
| Mean | 13 | 17 |
| S.D. | 3 | 2 |
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From the two regression equations, find r, `bar x and bar y`. 4y = 9x + 15 and 25x = 4y + 17
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| X | Y | |
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| Variance | 150 | 165 |
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Choose the correct alternative:
If byx < 0 and bxy < 0, then r is ______
Choose the correct alternative:
bxy and byx are ______
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 = ______
Choose the correct alternative:
Both the regression coefficients cannot exceed 1
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
State whether the following statement is True or False:
Cov(x, x) = Variance of x
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The geometric mean of negative regression coefficients is ______
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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`
