# 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 Coeffi - Mathematics and Statistics

Sum

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?

#### Solution

Given, bar(x) = 10, bar(y) = 90, sigma_x^2 = 9, sigma_y^2 = 144, r = 0.8

∴ sigma_x = 3, sigma_y = 12

byx = "r" sigma_y/sigma_x = 0.8 xx 12/3 = 0.8 × 4 = 3.2

bxy = "r" sigma_x/sigma_y = 0.8 xx 3/12 = 0.8 × 0.25 = 0.2

The regression equation of Y on X is

("Y" - bary) = "b"_(yx) ("X" - barx)

∴ (Y – 90) = 3.2 (X – 10)

∴ Y – 90 = 3.2 X – 32

∴ Y = 3.2 X – 32 + 90

∴ Y = 3.2 X + 58    ......(i)

The regression equation of X on Y is

("X" - barx) = "b"_(xy) ("Y" - bary)

∴ (X – 10) = 0.2 (Y – 90)

∴ X – 10 = 0.2 Y – 18

∴ X = 0.2 Y – 18 + 10

∴ X = 0.2 Y – 8    ......(ii)

When the company wants to attain the sales target of ₹ 150 lakhs,

Put Y = 150 lakh in equation (ii)

∴ X = 0.2 × 150 – 8 = 30 – 8 = 22

∴ The advertising budget should be ₹ 22 lakhs if the company wants to attain the sales target of ₹ 150 lakhs.

Concept: Properties of Regression Coefficients
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Chapter 2.3: Linear Regression - Q.4
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