Advertisements
Advertisements
Question
The data obtained on X, the length of time in weeks that a promotional project has been in progress at a small business, and Y, the percentage increase in weekly sales over the period just prior to the beginning of the campaign.
| X | 1 | 2 | 3 | 4 | 1 | 3 | 1 | 2 | 3 | 4 | 2 | 4 |
| Y | 10 | 10 | 18 | 20 | 11 | 15 | 12 | 15 | 17 | 19 | 13 | 16 |
Find the equation of the regression line to predict the percentage increase in sales if the campaign has been in progress for 1.5 weeks.
Solution
Here, X = Length of time in weeks,
Y = Percentage increase in weekly sales
| X = xi | Y = yi | `x_i^2` | xi yi |
| 1 | 10 | 1 | 10 |
| 2 | 10 | 4 | 20 |
| 3 | 18 | 9 | 54 |
| 4 | 20 | 16 | 80 |
| 1 | 11 | 1 | 11 |
| 3 | 15 | 9 | 45 |
| 1 | 12 | 1 | 12 |
| 2 | 15 | 4 | 30 |
| 3 | 17 | 9 | 51 |
| 4 | 19 | 16 | 76 |
| 2 | 13 | 4 | 26 |
| 4 | 16 | 16 | 64 |
| 30 | 176 | 90 | 479 |
From the table, we have
n = 12, ∑ xi = 30, ∑ yi = 176, `sum x_i^2 = 90`, ∑ xi yi = 479
∴ `bar x = (sum x_i)/"n" = 30/12 = 2.5`
`bar y = (sum y_i)/"n" = 176/12 = 14.67`
Now, `"b"_"YX" = (sum"x"_"i" "y"_"i" - "n" bar "x" bar "y")/(sum "x"_"i"^2 - "n" bar "x"^2)`
`= (479 - 12 xx 2.5 xx 14.67)/(90 - 12 xx (2.5)^2)`
`= (479 - 440.1)/(90 - 75) = 38.9/15 = 2.59`
Also,
`"a" = bar y - "b"_"YX" bar x`
= 14.67 - 2.59 × 2.5 = 14.67 - 6.475 = 8.195
∴ a ≈ 8.2
∴ The regression equation of percentage increase in weekly sales (Y) on length of weeks (X) is
Y = a + bYX + X
i.e., Y = 8.2 + 2.59 X
For X = 1.5, we get
Y = 8.2 + 2.59(1.5) = 8.2 + 3.885 = 12.085
∴ Increase in sales is 12.085% if the campaign has been in progress for 1.5 weeks.
APPEARS IN
RELATED QUESTIONS
The equations given of the two regression lines are 2x + 3y - 6 = 0 and 5x + 7y - 12 = 0.
Find:
(a) Correlation coefficient
(b) `sigma_x/sigma_y`
Find the feasible solution for the following system of linear inequations:
0 ≤ x ≤ 3, 0 ≤ y ≤ 3, x + y ≤ 5, 2x + y ≥ 4
Compute the product moment coefficient of correlation for the following data:
n = 100, `bar x` = 62, `bary` = 53, `sigma_x` = 10, `sigma_y` = 12
`Sigma (x_i - bar x) (y_i - bary) = 8000`
Information on v:ehicles [in thousands) passing through seven different highways during a day (X) and number of accidents reported (Y) is given as follows :
`Sigmax_i` = 105, `Sigmay_i` = 409, n = 7, `Sigmax_i^2` = 1681, `Sigmay_i^2` = 39350 `Sigmax_iy_i` = 8075
Obtain the linear regression of Y on X.
The two lines of regressions are x + 2y – 5 = 0 and 2x + 3y – 8 = 0 and the variance of x is 12. Find the variance of y and the coefficient of correlation.
For the given lines of regression, 3x – 2y = 5 and x – 4y = 7, find:
(a) regression coefficients byx and bxy
(b) coefficient of correlation r (x, y)
Calculate the Spearman’s rank correlation coefficient for the following data and interpret the result:
| X | 35 | 54 | 80 | 95 | 73 | 73 | 35 | 91 | 83 | 81 |
| Y | 40 | 60 | 75 | 90 | 70 | 75 | 38 | 95 | 75 | 70 |
For the following bivariate data obtain the equations of two regression lines:
| X | 1 | 2 | 3 | 4 | 5 |
| Y | 5 | 7 | 9 | 11 | 13 |
Given the following data, obtain a linear regression estimate of X for Y = 10, `bar x = 7.6, bar y = 14.8, sigma_x = 3.2, sigma_y = 16` and r = 0.7
bYX is ______.
If for bivariate data `bar x = 10, bar y = 12,` v(x) = 9, σy = 4 and r = 0.6 estimate y, when x = 5.
Identify the regression equations of x on y and y on x from the following equations, 2x + 3y = 6 and 5x + 7y − 12 = 0
If for a bivariate data byx = – 1.2 and bxy = – 0.3 then find r.
From the two regression equations y = 4x – 5 and 3x = 2y + 5, find `bar x and bar y`.
Regression equation of X on Y is ______
In the regression equation of Y on X, byx represents slope of the line.
Choose the correct alternative:
The slope of the line of regression of y on x is called the ______
Choose the correct alternative:
If the lines of regression of Y on X is y = `x/4` and X on Y is x = `y/9 + 1` then the value of r is
State whether the following statement is True or False:
The equations of two regression lines are 10x – 4y = 80 and 10y – 9x = 40. Then bxy = 0.9
State whether the following statement is True or False:
If equation of regression lines are 3x + 2y – 26 = 0 and 6x + y – 31= 0, then mean of X is 7
The equations of the two lines of regression are 2x + 3y − 6 = 0 and 5x + 7y − 12 = 0. Identify the regression lines
The equations of the two lines of regression are 6x + y − 31 = 0 and 3x + 2y – 26 = 0. Calculate the mean values of x and y
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 means are 136 and 148 respectively. The sum of product of deviations from respective means is 122. Obtain the regression equation of x on y
If n = 5, Σx = Σy = 20, Σx2 = Σy2 = 90, Σxy = 76 Find the regression equation of x on y
The regression equation of x on y is 40x – 18y = 214 ......(i)
The regression equation of y on x is 8x – 10y + 66 = 0 ......(ii)
Solving equations (i) and (ii),
`barx = square`
`bary = square`
∴ byx = `square/square`
∴ bxy = `square/square`
∴ r = `square`
Given variance of x = 9
∴ byx = `square/square`
∴ `sigma_y = square`
If `(x - 1)/l = (y - 2)/m = (z + 1)/n` is the equation of the line through (1, 2, -1) and (-1, 0, 1), then (l, m, n) is ______
If `bar"X"` = 40, `bar"Y"` = 6, σx = 10, σy = 1.5 and r = 0.9 for the two sets of data X and Y, then the regression line of X on Y will be:
The management of a large furniture store would like to determine sales (in thousands of ₹) (X) on a given day on the basis of number of people (Y) that visited the store on that day. The necessary records were kept, and a random sample of ten days was selected for the study. The summary results were as follows:
`sumx_i = 370 , sumy_i = 580, sumx_i^2 = 17200 , sumy_i^2 = 41640, sumx_iy_i = 11500, n = 10`
Out of the two regression lines x + 2y – 5 = 0 and 2x + 3y = 8, find the line of regression of y on x.
XYZ company plans to advertise some vacancies. The Manager is asked to suggest the monthly salary for these vacancies based on the years of experience. To do so, the Manager studies the years of service and the monthly salary drawn by the existing employees in the company.
Following is the data that the Manager refers to:
| Years of service (X) | 11 | 7 | 9 | 5 | 8 | 6 | 10 |
| Monthly salary (in ₹ 1000)(Y) | 10 | 8 | 6 | 5 | 9 | 7 | 11 |
- Find the regression equation of monthly salary on the years of service.
- If a person with 13 years of experience applies for a job in this company, what monthly salary will be suggested by the Manager?
