Advertisements
Advertisements
प्रश्न
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.
Advertisements
उत्तर
Given: n =7, ∑(xi - 70) = - 35, ∑(yi - 60) = - 7,
∑(xi - 70)2 = 2989, ∑(yi - 60)2 = 476,
∑(xi - 70)(yi - 60) = 1064
Let ui = xi - 70 and vi = yi - 60
∴ ∑ ui = - 35, ∑ vi = - 7
`sum "u"_"i"^2 = 2989, sum "v"_"i"^2 = 479`
∑ ui vi = 1064
∴ `bar "u" = (sum "u"_"i")/"n" = (-35)/7 = - 5`
∴ `bar "v" = (sum "v"_"i")/"n" = (-7)/7 = - 1`
Now, `sigma_"u"^2 = (sum "u"_"i"^2)/"n" - (bar"u")^2`
`= 2989/7 - (- 5)^2` = 427 - 25 = 402
and `sigma_"v"^2 = (sum "v"_"i"^2)/"n" - (bar"v")^2`
`= 476/7 - (- 1)^2 = 68 - 1 = 67`
cov(u, v) = `(sum "u"_"i" "v"_"i")/"n" - bar"uv"`
`= 1064/7 - (- 5)(- 1)` = 152 - 5 = 147
Since the regression coefficients are independent of change of origin,
bYX = bVU and bXY = bUV
∴ bYX = bVU = `("cov" ("u", "v"))/sigma_"U"^2 = 147/402 = 0.36`
and bXY = bUV = `("cov" ("u", "v"))/sigma_"V"^2 = 147/67 = 2.19`
Also, `bar x = bar u` + 70 = - 5 + 70 = 65
and `bar y = bar v` + 60 = - 1 + 60 = 59
(i) The line of regression of Y on X is
`("Y" - bar y) = "b"_"YX" ("X" - bar x)`
∴ (Y - 59) = (0.36)(X - 65)
∴ Y - 59 = 0.36X - 23.4
∴ Y = 0.36X + 59 - 23.4
∴ Y = 0.36X + 35.6
(ii) The line of regression of X on Y is
`("X" - bar x) = "b"_"XY" ("Y" - bar y)`
∴ (X - 65) = (2.19)(Y - 59)
∴ X - 65 = 2.19Y - 129.21
∴ X = 2.19Y + 65 - 129.21
∴ X = 2.19Y - 64.21
(iii) r = `+-sqrt("b"_"YX" * "b"_"XY")`
`= +- sqrt((0.36)(2.19))`
`= +- sqrt0.7884 = +- 0.8879`
Since bYX and bXY both are positive,
r is also positive.
∴ r = 0.8879
APPEARS IN
संबंधित प्रश्न
For bivariate data. `bar x = 53`, `bar y = 28`, byx = −1.2, bxy = −0.3. Find 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
- Obtain the two regression equations.
- 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 = 1.9 and bXY = - 0.25
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
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.
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.
For certain X and Y series, which are correlated the two lines of regression are 10y = 3x + 170 and 5x + 70 = 6y. Find the correlation coefficient between them. Find the mean values of X and Y.
Choose the correct alternative:
If the regression equation X on Y is 3x + 2y = 26, then bxy equal to
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 byx = 1.5 and bxy = `1/3` then r = `1/2`, the given data is consistent
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:
If u = x – a and v = y – b then bxy = buv
State whether the following statement is True or False:
Regression coefficient of x on y is the slope of regression line of x on y
|bxy + byx| ≥ ______
The value of product moment correlation coefficient between x and x is ______
If u = `(x - 20)/5` and v = `(y - 30)/4`, then byx = ______
The equations of two lines of regression are 3x + 2y – 26 = 0 and 6x + y – 31 = 0. Find variance of x if variance of y is 36
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)`
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`
| 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 + byz| ≥ ______.
