Advertisements
Advertisements
Question
Using the following information you are requested to
- obtain the linear regression of Y on X
- Estimate the level of defective parts delivered when inspection expenditure amounts to ₹ 82
∑X = 424, ∑Y = 363, ∑X2 = 21926, ∑Y2 = 15123, ∑XY = 12815, N = 10.
Here X is the expenditure on inspection, Y is the defective parts delivered.
Solution
Given ∑X = 424, ∑Y = 363, ∑X2 = 21926, ∑Y2 = 15123, ∑XY = 12815, N = 10.
`bar"X" = (sum"X")/"N" = 424/10` = 42.4
`bar"Y" = (sum"Y")/"N" = 363/10` = 36.3
Regression coefficient of Y on X is
byx = `("N"sum"XY" - (sum"X")(sum"Y"))/("N"sum"X"^2 - (sum"X")^2)`
= `(10(12815) - (424)(363))/(10(21926) - (424)^2)`
= `(128150 - 153912)/(219260 - 179776)`
= `(-25762)/39484`
= − 0.652
∴ Regression line of Y on X is
`"Y" - bar"Y" = "b"_"yx"("X" - bar"X")`
Y − 36.3 = − 0.652 (X − 42.4)
Y − 36.3 = − 0.652X + 27.645
Y = − 0.652X + 63.945
When X = 82, Y = − 0.652(82) + 63.945
Y = − 53.464 + 63.945
Y = 10.481
Y ≈ 10
APPEARS IN
RELATED QUESTIONS
From the data given below:
Marks in Economics: | 25 | 28 | 35 | 32 | 31 | 36 | 29 | 38 | 34 | 32 |
Marks in Statistics: | 43 | 46 | 49 | 41 | 36 | 32 | 31 | 30 | 33 | 39 |
Find
- The two regression equations,
- The coefficient of correlation between marks in Economics and Statistics,
- The mostly likely marks in Statistics when the marks in Economics is 30.
The heights (in cm.) of a group of fathers and sons are given below:
Heights of fathers: | 158 | 166 | 163 | 165 | 167 | 170 | 167 | 172 | 177 | 181 |
Heights of Sons: | 163 | 158 | 167 | 170 | 160 | 180 | 170 | 175 | 172 | 175 |
Find the lines of regression and estimate the height of the son when the height of the father is 164 cm.
The following data give the height in inches (X) and the weight in lb. (Y) of a random sample of 10 students from a large group of students of age 17 years:
X | 61 | 68 | 68 | 64 | 65 | 70 | 63 | 62 | 64 | 67 |
Y | 112 | 123 | 130 | 115 | 110 | 125 | 100 | 113 | 116 | 125 |
Estimate weight of the student of a height 69 inches.
Given the following data, what will be the possible yield when the rainfall is 29.
Details | Rainfall | Production |
Mean | 25`` | 40 units per acre |
Standard Deviation | 3`` | 6 units per acre |
Coefficient of correlation between rainfall and production is 0.8.
The following data relate to advertisement expenditure (in lakh of rupees) and their corresponding sales (in crores of rupees)
Advertisement expenditure | 40 | 50 | 38 | 60 | 65 | 50 | 35 |
Sales | 38 | 60 | 55 | 70 | 60 | 48 | 30 |
Estimate the sales corresponding to advertising expenditure of ₹ 30 lakh.
The regression coefficient of X on Y
The lines of regression of X on Y estimates
The lines of regression intersect at the point
The term regression was introduced by
X and Y are a pair of correlated variables. Ten observations of their values (X, Y) have the following results. ∑X = 55, ∑XY = 350, ∑X2 = 385, ∑Y = 55, Predict the value of y when the value of X is 6.