• QR Code (size=2)
• QR Code (size=3)
• QR Code (size=4)
• QR Code (size=5)
• QR Code (size=6)

10
9
12
14
6
13
12
13
6
12
10
9
12
7
10
11
15
10
12
10
12
11
11
12
15
12
11
9
11
11
9
15
12
9
12
12
9
9
11
12
12
12
12
6
11
12
9
11
9
10
10
9
12
11
9
9
12
6
10
12
11
14
8
9
10
10
10
11
10
12
14
10
8
8
7
11
6
9
12
12
12
9
15
15
13
9
12
9
15
11
11
6
14
11
8
10
10
9
8
9
10
11
14
12
9
13
8
12
14
9
10
12
12
9
9
12
15
12
11
8
11
11
10
12
9
11
15
14
6
9
9
8
7
10
6
9
9
7
11
9
12
9
10
11
7
12
8
13
11
11
12
11
12
3
10
13
10
6
11
12
9
10
15
9
6
9
15
15
9
11
9
11
10
9
6
12
13
12
12

library(MASS)
library(car)
par1 <- as.numeric(par1)
if (par2 == '0') par2 = 'Sturges' else par2 <- as.numeric(par2)
x <- as.ts(x) #otherwise the fitdistr function does not work properly
r <- fitdistr(x,'normal')
print(r)
bitmap(file='test1.png')
myhist<-hist(x,col=par1,breaks=par2,main=main,ylab=ylab,xlab=xlab,freq=F)
curve(1/(r$estimate[2]*sqrt(2*pi))*exp(-1/2*((x-r$estimate[1])/r$estimate[2])^2),min(x),max(x),add=T)
dev.off()
bitmap(file='test3.png')
qqPlot(x,dist='norm',main='QQ plot (Normal) with confidence intervals')
grid()
dev.off()
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Parameter',1,TRUE)
a<-table.element(a,'Estimated Value',1,TRUE)
a<-table.element(a,'Standard Deviation',1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'mean',header=TRUE)
a<-table.element(a,r$estimate[1])
a<-table.element(a,r$sd[1])
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'standard deviation',header=TRUE)
a<-table.element(a,r$estimate[2])
a<-table.element(a,r$sd[2])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')