How to do part f naval bases of similar size the recently expanded their fleets.

Question

How to do part f

naval bases of similar size the recently expanded their fleets. NAVALBASE PERCENTAGE COST OF 1MPROVEMENT AT MODIFYING FLEET END OF DECADE y x.milions of dollars BASE LOCATION U.S U.S U.S U.s 18 32 125 160 ine 162 110 37 ine mo- e to Foreign Foreign Foreign Foreign Foreign 30 10 25 140 85 50 used uced sults 0. Is 2 (a) Fit the quadratic model to the data. (b) Interpret the value of R on the printout. (c) Find the value of s and interpret it. differ (d) Perform a test of overall model adequacy. Use aron- 1993) iables n clay levels dentify (e) Is there sufficient evidence to conclude that the percentage improvement y increases more quickly for more costly fleet modifications than for less costly teet modifications? Test with -,05. (f) Now epnsider the complete second-order model e, chlo- where ent vari for E(y) d at ive Mad -Cost of modifying the fieet 1 irU.S. base o it foreign base

Explanation / Answer

part (f) Rcodes with output :

Enter the data in Excel and save as .csv file.

> data1=read.csv(file.choose(),header=T) #importing excel file
> data1
y x1 x2
1 18 125 1
2 32 160 1
3 9 80 1
4 37 162 1
5 6 110 1
6 3 90 0
7 30 140 0
8 10 85 0
9 25 150 0
10 2 50 0
> attach(data1) #attaching the dataset
> x12=x1^2
> x1x2=x1*x2
> x12x2=x12*x2
> x12
[1] 15625 25600 6400 26244 12100 8100 19600 7225 22500 2500
> x1x2
[1] 125 160 80 162 110 0 0 0 0 0
> x12x2
[1] 15625 25600 6400 26244 12100 0 0 0 0 0

> model=lm(y~x1+x12+x2+x1x2+x12x2)
> summary(model)

Call:
lm(formula = y ~ x1 + x12 + x2 + x1x2 + x12x2)

Residuals:
1 2 3 4 5 6 7 8 9 10
3.7601 -2.0945 0.7632 1.3696 -3.7984 -5.0075 5.4478 3.1274 -3.9947 0.4269

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.031900 22.645016 0.090 0.933
x1 -0.103639 0.485127 -0.214 0.841
x12 0.001889 0.002338 0.808 0.464
x2 49.766861 52.369300 0.950 0.396
x1x2 -0.874758 0.935755 -0.935 0.403
x12x2 0.003534 0.003979 0.888 0.425

Residual standard error: 5.387 on 4 degrees of freedom
Multiple R-squared: 0.9233, Adjusted R-squared: 0.8274
F-statistic: 9.631 on 5 and 4 DF, p-value: 0.02379

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