The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a function of the cost x of modifying the fleet. A first proposal is the quadratic model E(y) = β0 + β1x + β2x2 Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers?
The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a function of the cost x of modifying the fleet. A first proposal is the quadratic model E(y) = β0 + β1x + β2x2 Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a
E(y) = β0 + β1x + β2x2
- Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers?

Transcribed Image Text:a) Fit the model to the data, then construct a residual plot versus x. Do you detect any
trends? Any outliers?
E(y) = Bo + Bix + B2x?
E(y) = (-18.62) + (0.31)x + B2x?
x|
125
160
80
162
110
90
140
85
150
50
1152
y|
xy 2250
x2 | 15625 25600 6400 26244 12100 8100 19600 7225 22500 2500 = 145,894
18
32
37
6
3
30
10
25
2
172
5120
720
5994
660 270 4200
850
3750 100 = 23,914
B1= nxy - xx
nx - (Ex)?
B1= 10 (23,914) – (1152)( 172)
10 (145,894) – (1152)2
Bo= 172 - (0.31...)(1152)
B1= 239140 – 198144
10
1458940 – 1327104
Bo= 172 – 358.2283443065627
B1= 40996
10
131836
Bo = (-18.62283443065627)
B1= 0.3109621044327801
Bo= (-18.62)
B1= 0.31
Normal P-P Plot of Regression Standardized Residual
Dependent Variable: IMPROVE
10
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