The exercise involving data in this and subsequent sections were designed to be solved using Excel. In a regression analysis involving 30 observations, the following estimated regression equation was obtained. Enter negative values as negative numbers. ŷ = 17.6 + 3.8z1 – 2.3zz + 7.6x3 +2.74 a. Interpret b1, b2, b3, and b4 in this estimated regression equation. Assume that for each coefficient statement, the remaining three variables are held constant (to 1 decimal). 3.8 estimated change in y per 1 unit change in #1 b2 = -2.3 estimated change in y per 1 unit change in æ2 b3 7.6 estimated change in y per 1 unit change in #3 b4 = 2.7 estimated change in y per 1 unit change in #4 b. Estimate y when ¤1 = 10, x2 = 5, æz = 1, and #4 = 2. (to 1 decimal)
The exercise involving data in this and subsequent sections were designed to be solved using Excel. In a regression analysis involving 30 observations, the following estimated regression equation was obtained. Enter negative values as negative numbers. ŷ = 17.6 + 3.8z1 – 2.3zz + 7.6x3 +2.74 a. Interpret b1, b2, b3, and b4 in this estimated regression equation. Assume that for each coefficient statement, the remaining three variables are held constant (to 1 decimal). 3.8 estimated change in y per 1 unit change in #1 b2 = -2.3 estimated change in y per 1 unit change in æ2 b3 7.6 estimated change in y per 1 unit change in #3 b4 = 2.7 estimated change in y per 1 unit change in #4 b. Estimate y when ¤1 = 10, x2 = 5, æz = 1, and #4 = 2. (to 1 decimal)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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I need help with part B
![The exercise involving data in this and subsequent sections were designed to be solved using Excel.
In a regression analysis involving 30 observations, the following estimated regression equation was obtained. Enter negative values as negative
numbers.
ŷ = 17.6 + 3.821 – 2.3x2 + 7.6x3 + 2.7x4
a. Interpret b1, b , b3, and bą in this estimated regression equation. Assume that for each coefficient statement, the remaining three variables
are held constant (to 1 decimal).
b, =
3.8
estimated change in y per 1 unit change in a1
b2 :
-2.3
estimated change in y per 1 unit change in a2
b3 :
7.6
estimated change in y per 1 unit change in 13
b4 =
2.7
estimated change in y per 1 unit change in ¤4
b. Estimate y when ¤1 = 10, x2 = 5, x3 = 1, and æ4 = 2. (to 1 decimal)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5aa35589-0e2e-46e3-880e-5b8722d722b0%2F6c899eca-a19f-41ea-af24-052233cc8341%2F4dw84ed_processed.png&w=3840&q=75)
Transcribed Image Text:The exercise involving data in this and subsequent sections were designed to be solved using Excel.
In a regression analysis involving 30 observations, the following estimated regression equation was obtained. Enter negative values as negative
numbers.
ŷ = 17.6 + 3.821 – 2.3x2 + 7.6x3 + 2.7x4
a. Interpret b1, b , b3, and bą in this estimated regression equation. Assume that for each coefficient statement, the remaining three variables
are held constant (to 1 decimal).
b, =
3.8
estimated change in y per 1 unit change in a1
b2 :
-2.3
estimated change in y per 1 unit change in a2
b3 :
7.6
estimated change in y per 1 unit change in 13
b4 =
2.7
estimated change in y per 1 unit change in ¤4
b. Estimate y when ¤1 = 10, x2 = 5, x3 = 1, and æ4 = 2. (to 1 decimal)
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