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The HRD manager of a company wants to find a measure which he can use to fix the monthly income of persons applying for the job in the production department. - Mathematics and Statistics

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प्रश्न

The HRD manager of a company wants to find a measure which he can use to fix the monthly income of persons applying for the job in the production department. As an experimental project, he collected data of 7 persons from that department referring to years of service and their monthly incomes.

Years of service (X) 11 7 9 5 8 6 10
Monthly Income (₹ 1000's)(Y) 10 8 9 5 9 7 11
  1. Find the regression equation of income on years of service.
  2. What initial start would you recommend for a person applying for the job after having served in a similar capacity in another company for 13 years?
योग
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उत्तर

(i) Here, X = Years of service,

Y = Income (₹ in 1000’s)

X = xi Y = yi `"x"_"i"^2` xi yi
11 10 121 110
7 8 49 56
9 6 81 54
5 5 25 25
8 9 64 72
6 7 36 42
10 11 100 110
56 56 476 469

From the table, we have

n = 7, ∑ xi = 56, ∑ yi = 56, `sum"x"_"i"^2` = 476,
∑ xi yi = 469

`bar"x" = sum "x"_"i"/"n" = 56/7 = 8`

`bar"y" = sum "y"_"i"/"n" = 56/7 = 8`

Now, `"b"_"YX" = (sum"x"_"i" "y"_"i" - "n" bar "x" bar "y")/(sum "x"_"i"^2 - "n" bar"x"^2)`

∴ `"b"_"YX" = (469 - 7 xx 8 xx 8)/(476 - 7 xx (8)^2) = (469 -448)/(476 - 448) = 21/28 = 3/4`

∴ `"b"_"YX"` = 0.75

Also, a = `bar"y" - "b"_"YX"  bar "x" = 8 - 0.75 xx 8 = 8 - 6 = 2`

∴ The regression equation of income (Y) on years of service (X) is

Y = a + bYX X

∴ Y = 2 + 0.75 X

(ii) Given, years of service (X) = 13

∴ Substituting X = 13 in regression equation, we get

Y = 2 + 0.75 (13)

∴ Y = 2 + 9.75

∴ Y = 11.75 (₹ in 1000’s)

∴ I would recommend an initial start of ₹ 11,750 for a person who has served in similar capacity in another company for 13 years.

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Types of Linear Regression
  क्या इस प्रश्न या उत्तर में कोई त्रुटि है?
अध्याय 3: Linear Regression - Exercise 3.1 [पृष्ठ ४१]

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बालभारती Mathematics and Statistics 2 (Commerce) [English] Standard 12 Maharashtra State Board
अध्याय 3 Linear Regression
Exercise 3.1 | Q 1 | पृष्ठ ४१

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