Advertisements
Advertisements
Question
Compute the appropriate regression equation for the following data:
x (Dependent Variable) | 10 | 12 | 13 | 17 | 18 |
y (Independent Variable) | 5 | 6 | 7 | 9 | 13 |
Solution
X = xi | Y = yi | xi2 | yi2 | xiyi | |
10 | 5 | 100 | 25 | 50 | |
12 | 6 | 144 | 36 | 72 | |
13 | 7 | 169 | 49 | 91 | |
17 | 9 | 289 | 81 | 153 | |
18 | 13 | 324 | 169 | 234 | |
Total | 70 | 40 | 1026 | 360 | 600 |
From the table, we have,
n = 5, Σxi = 70, Σyi = 40, Σxiyi = 600, Σxi2 = 1026, Σyi2 = 360
`barx = (sumx_"i")/"n" = 70/5` = 14, `bary = (sumy_"i")/"n" = 40/5` = 8
Now, for regression equation of X on Y
bxy = `(sumx_"i"y_"i" - "n"bar(x) bar(y))/(sumy_"i"^2 - "n" bar(y)^(-2))`
= `(600 - 5 xx 14 xx 8)/(360 - 5(8)^2)`
= `(600 - 560)/(360 - 320)`
= `40/40`
= 1
Also, a' = `barx - "b"_(xy) bary` = 14 – 1 (8)
= 14 – 8
= 6
∴ The regression equation of X on Y is
X = a' + bxy Y
∴ X = 6 + Y
APPEARS IN
RELATED QUESTIONS
Choose the correct alternative:
There are ______ types of regression equations
Calculate the regression equations of X on Y and Y on X from the following data:
X | 10 | 12 | 13 | 17 | 18 |
Y | 5 | 6 | 7 | 9 | 13 |
The following table gives the aptitude test scores and productivity indices of 10 workers selected at random.
Aptitude score (X) | 60 | 62 | 65 | 70 | 72 | 48 | 53 | 73 | 65 | 82 |
Productivity Index (Y) | 68 | 60 | 62 | 80 | 85 | 40 | 52 | 62 | 60 | 81 |
Obtain the two regression equations and estimate the productivity index of a worker whose test score is 95.
The following table gives the aptitude test scores and productivity indices of 10 workers selected at random.
Aptitude score (X) | 60 | 62 | 65 | 70 | 72 | 48 | 53 | 73 | 65 | 82 |
Productivity Index (Y) | 68 | 60 | 62 | 80 | 85 | 40 | 52 | 62 | 60 | 81 |
Obtain the two regression equations and estimate the test score when the productivity index is 75.
The following are the marks obtained by the students in Economics (X) and Mathematics (Y)
X | 59 | 60 | 61 | 62 | 63 |
Y | 78 | 82 | 82 | 79 | 81 |
Find the regression equation of Y on X.
For the following data, find the regression line of Y on X
X | 1 | 2 | 3 |
Y | 2 | 1 | 6 |
Hence find the most likely value of y when x = 4.
From the following data, find the regression equation of Y on X and estimate Y when X = 10.
X | 1 | 2 | 3 | 4 | 5 | 6 |
Y | 2 | 4 | 7 | 6 | 5 | 6 |
Choose the correct alternative.
If u = `("x - a")/"c" and "v" = ("y - b")/"d" "then" "b"_"yx"` = _________
Choose the correct alternative.
byx = ______
Choose the correct alternative.
Cov (x, y) = __________
Choose the correct alternative.
If bxy < 0 and byx < 0 then 'r' is __________
Fill in the blank:
If bxy < 0 and byx < 0 then ‘r’ is __________
Fill in the blank:
There are __________ types of regression equations.
Fill in the blank:
Corr (x, −x) = __________
Fill in the blank:
If u = `"x - a"/"c" and "v" = "y - b"/"d"` then byx = _______
Fill in the blank:
|bxy + byx| ≥ ______
Fill in the blank:
bxy . byx = _______
State whether the following statement is True or False.
Regression equation of Y on X is `("y" - bar "y") = "b"_"yx" ("x" - bar "x")`