Advertisements
Advertisements
Question
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
- Mean values of X and Y
- Standard deviation of Y
- Coefficient of correlation between X and Y.
Advertisements
Solution
Given, `sigma_"X"^2 = 25`
∴ `sigma_"X"` = 5
Regression equation of Y on X is
5y – x = 22
Regression equation of X on Y is
64x - 45y = 22
(i) Consider, the two regression equation
- x + 5y = 22 ....(i)
64x - 45y = 22 ....(ii)
By (i) × + (ii), we get
- 9x + 45y = 198
+ 64x - 45y = 22
55x = 220
∴ x = 4
Substituting x = 4 in (i), we get
- 4 + 5y = 22
∴ 5y = 22 + 4
∴ y = `26/5 = 5.2`
Since the point of intersection of two regression lines is `(bar x, bar y)`,
`bar x` = mean value of X = 4 and
`bar y` = mean value of Y = 5.2
(ii) To find standard deviation of Y we should first find the coefficient of correlation between X and Y.
Regression equation of Y on X is
5y - x = 22
i.e., 5Y = X + 22
i.e., Y = `"X"/5 + 22/5`
Comparing it with Y = bYX X + a, we get
`"b"_"YX" = 1/5`
Now, regression equation of X on Y is
64x - 45y = 22
i.e., 64X - 45Y = 22
i.e., 64X = 45Y + 22
i.e., X = `"45Y"/64 + 22/64`
Comparing it with X = bXY Y + a', we get
`"b"_"XY" = 45/64`
r = `+-sqrt("b"_"XY" * "b"_"YX")`
`= +- sqrt((1/5)(45/64)) = +- sqrt(9/64) = +- 3/8`
Since bYX and bXY are positive,
r is also positive.
∴ r = `3/8= 0.375`
∴ `sigma_"Y"`= Standard deviation of Y = 0.375
(iii) The correlation coefficient of X and Y =
Now, `"b"_"YX" = ("r". sigma_"Y")/sigma_"X"`
∴ `1/5 = 3/8 xx sigma_"Y"/5`
∴ `sigma_"Y" = 8/3`
APPEARS IN
RELATED QUESTIONS
For bivariate data. `bar x = 53, bar y = 28, "b"_"YX" = - 1.2, "b"_"XY" = - 0.3` Find estimate of Y for X = 50.
For bivariate data. `bar x = 53, bar y = 28, "b"_"YX" = - 1.2, "b"_"XY" = - 0.3` Find estimate of X for Y = 25.
Bring out the inconsistency in the following:
bYX + bXY = 1.30 and r = 0.75
For a certain bivariate data
| X | Y | |
| Mean | 25 | 20 |
| S.D. | 4 | 3 |
And r = 0.5. Estimate y when x = 10 and estimate x when y = 16
Given the following information about the production and demand of a commodity obtain the two regression lines:
| X | Y | |
| Mean | 85 | 90 |
| S.D. | 5 | 6 |
The coefficient of correlation between X and Y is 0.6. Also estimate the production when demand is 100.
Two samples from bivariate populations have 15 observations each. The sample means of X and Y are 25 and 18 respectively. The corresponding sum of squares of deviations from respective means is 136 and 150. The sum of the product of deviations from respective means is 123. Obtain the equation of the line of regression of X on Y.
An inquiry of 50 families to study the relationship between expenditure on accommodation (₹ x) and expenditure on food and entertainment (₹ y) gave the following results:
∑ x = 8500, ∑ y = 9600, σX = 60, σY = 20, r = 0.6
Estimate the expenditure on food and entertainment when expenditure on accommodation is Rs 200.
In a partially destroyed laboratory record of an analysis of regression data, the following data are legible:
Variance of X = 9
Regression equations:
8x − 10y + 66 = 0
and 40x − 18y = 214.
Find on the basis of above information
- The mean values of X and Y.
- Correlation coefficient between X and Y.
- Standard deviation of Y.
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.
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`
If bYX = − 0.6 and bXY = − 0.216, then find correlation coefficient between X and Y. Comment on it.
Choose the correct alternative:
If for a bivariate data, bYX = – 1.2 and bXY = – 0.3, then r = ______
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, σy2 = 16, then bxy = ______
|bxy + byx| ≥ ______
The value of product moment correlation coefficient between x and x is ______
Arithmetic mean of positive values of regression coefficients is greater than or equal to ______
If u = `(x - 20)/5` and v = `(y - 30)/4`, then byx = ______
The geometric mean of negative regression coefficients is ______
byx is the ______ of regression line of y on x
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`
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`
| 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`
bXY . bYX = ______.
