(a) half normal:

A<-c(-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1)
B<-c(-1,-1,1,1,-1,-1,1,1,-1,-1,1,1,-1,-1,1,1)
C<-c(-1,-1,-1,-1,1,1,1,1,-1,-1,-1,-1,1,1,1,1)
D<-c(-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1,1,1,1)
obs<-c(12,18,13,20,1,25,15,25,10,24,13,24,19,21,17,23)
dat<-data.frame(A,B,C,D,obs)
library(DoE.base)
## Warning: package 'DoE.base' was built under R version 4.1.3
## 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
model<-lm(obs~A*B*C*D,data=dat)
halfnormal(model)
## 
## Significant effects (alpha=0.05, Lenth method):
## [1] A

Comment: From the half normal plot we see only effect (time)A is significant.

  1. ANOVA
anova_mod<-aov(obs~A,data=dat)
summary(anova_mod)
##             Df Sum Sq Mean Sq F value   Pr(>F)    
## A            1    400   400.0   22.05 0.000344 ***
## Residuals   14    254    18.1                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Comment: We see from anova Time(A) has a p- value 0.000344 which is less than 0.05. So we reject null hypothesis Ho. So time(A) has a significant with yield.