Question 11

Part A

Display Half Normal Plot

library(DoE.base)
## Warning: package 'DoE.base' was built under R version 4.2.2
## Loading required package: grid
## Loading required package: conf.design
## Registered S3 method overwritten by 'DoE.base':
##   method           from       
##   factorize.factor conf.design
## 
## Attaching package: 'DoE.base'
## The following objects are masked from 'package:stats':
## 
##     aov, lm
## The following object is masked from 'package:graphics':
## 
##     plot.design
## The following object is masked from 'package:base':
## 
##     lengths
FA<-rep(c(-1,1),8)
FB<-rep(c(-1,-1,1,1),4)
FC<-rep(c(-1,-1,-1,-1,1,1,1,1),2)
FD<-c(rep(-1,8), rep(1,8))
Obs_13<-c(12,18,13,20,17,25,15,25,10,24,13,24,19,21,17,23)
Data_13<-data.frame(FA,FB,FC,FD,Obs_13)
model_13<- lm(Obs_13~FA*FB*FC*FD, data = Data_13)
coef(model_13)
## (Intercept)          FA          FB          FC          FD       FA:FB 
##      18.500       4.000       0.250       1.750       0.375       0.250 
##       FA:FC       FB:FC       FA:FD       FB:FD       FC:FD    FA:FB:FC 
##      -0.750      -0.500       0.125       0.125      -0.625       0.500 
##    FA:FB:FD    FA:FC:FD    FB:FC:FD FA:FB:FC:FD 
##      -0.125      -1.375       0.125       0.375
halfnormal(model_13)
## 
## Significant effects (alpha=0.05, Lenth method):
## [1] FA       FC       FA:FC:FD

Comment: From Half-normal plot, we found that Factor A, Factor C and Interaction of Factor A:C:D are significant, so we can’t neglect Factor D due to interaction with Factor A and Factor C.

Part B

Model_132<- lm(Obs_13~FA+FC+FD+FA*FC+FA*FD+FC*FD+FA*FC*FD, data = Data_13)
coef(Model_132)
## (Intercept)          FA          FC          FD       FA:FC       FA:FD 
##      18.500       4.000       1.750       0.375      -0.750       0.125 
##       FC:FD    FA:FC:FD 
##      -0.625      -1.375
summary(Model_132)
## 
## Call:
## lm.default(formula = Obs_13 ~ FA + FC + FD + FA * FC + FA * FD + 
##     FC * FD + FA * FC * FD, data = Data_13)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##   -1.5   -1.0    0.0    1.0    1.5 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  18.5000     0.3187  58.050 8.61e-12 ***
## FA            4.0000     0.3187  12.551 1.52e-06 ***
## FC            1.7500     0.3187   5.491  0.00058 ***
## FD            0.3750     0.3187   1.177  0.27314    
## FA:FC        -0.7500     0.3187  -2.353  0.04643 *  
## FA:FD         0.1250     0.3187   0.392  0.70513    
## FC:FD        -0.6250     0.3187  -1.961  0.08550 .  
## FA:FC:FD     -1.3750     0.3187  -4.315  0.00256 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.275 on 8 degrees of freedom
## Multiple R-squared:  0.9645, Adjusted R-squared:  0.9334 
## F-statistic: 31.03 on 7 and 8 DF,  p-value: 3.475e-05

Comment: Here from summary of updates model, we found out that Factor A, Factor C and Interaction Factor A : Factor C and Factor A: Factor C : Factor D (Interaction ) is significant in model.