x=rnorm(n=1, mean=100, sd=15)
y=runif(n=3, min=1, max=10)
N = 10000
random.data = rnorm(N, mean=0, sd=1)
hist(random.data, nclass = 50, col = "navy", xlab = "Data",
probability = T, main = "Histogram of Random Data")
dens = density(random.data)
lines(dens, col = "orange", lwd = 4)
sample(1:10,3)
sample(c(“gu”,“choki”,“pa”),1)
sample(1:10)
sample(0:1, 10, replace=T)
# FOR loop
for (i_loop in 1:5) {
print(i_loop)
}
for (i_loop in 1:5) {
print(c(i_loop, 2^i_loop))
}
counter <- 1
while(counter<=10){
print(counter)
counter<-counter+1
}
counter <- 1
while(counter^2 <= 10){
print(c(counter, counter^2))
counter<-counter+1
}
affil<-"cogsci"
if (affil=="cogsci") {
print("you are wonderful")
}
affil<-"phil"
if (affil=="cogsci") {
print("you are wonderful")
} else {
print("still, you are wonderful")
}
counter=6
repeat{
print(counter)
counter = counter + 1
if(counter>5){break}
}
counter=6
repeat{
if(counter>5){break}
print(counter)
counter+counter+1
}
six.counter=0; N = 1000
for (i_loop in 1:N) {
die<-sample(1:6,1)
if (die==6) {six.counter=six.counter+1}
}
six.counter/N
N=1000; six.counter=rep(0,N);
for (i_loop in 1:N) {
die<-sample(1:6,1)
if (die==6) {six.counter[i_loop]=1}
}
plot(1:N,cumsum(six.counter)/(1:1000),type='l',ylim=c(0,1),
lwd=2)
abline(h=1/6,lwd=2,col='red')
N = 1000
die.all <- sample(1:6,N,replace=T)
six.index <- die.all==6
par(mfrow = c(2,1))
par(oma=c(2,2,0,0),mar=c(4,4,1,1),mfrow=c(2,1))
plot(1:N, die.all, pch=20, col = 'red', ylim = c(0,7),
ylab = "Result", xlab = "trial")
plot(1:N,cumsum(six.index)/(1:1000), type='l', ylim=c(0,1), lwd=2,
ylab = "P(die = 6)", xlab = "trial")
abline(h=1/6,lwd=2,col='red')
# CLT w/ loop
N=10;nRep=10000;
means<-rep(0,nRep)
for (i_rep in 1:nRep) {
dat<-runif(N)
means[i_rep]=mean(dat)
}
hist(means,nclass=50,probability=T)
dens<-density(means)
lines(dens,col='skyblue',lwd=3)
xs=seq(-0,1,0.01)
theo.dens<-dnorm(xs,mean=0.5,sd=sqrt((1/12)/N))
lines(xs,theo.dens,col='orange',lwd=3,lty=2)
# CLT w/o loop
N=10
nRep=10000
dat<-matrix(runif(N*nRep),nrow=N)
means<-colMeans(dat)
hist(means,nclass=50,probability=T)
dens<-density(means); lines(dens,col='skyblue',lwd=3)
xs=seq(-0,1,0.01)
theo.dens<-dnorm(xs,mean=0.5,sd=sqrt((1/12)/N))
lines(xs,theo.dens,col='orange',lwd=3,lty=2)
r=-99;v1=1633;v2=355
while (r!=0){
r=v1%%v2
print(paste('v1 =',v1,', v2 = ',v2,',remainder = ',r))
v1=v2
v2=r
}
tol = 1e-7;grad = 1e10; lambda = 0.1;x = 10; x.hist = x
grad = 2*x+2
while (abs(grad)>tol){
x = x - lambda*grad
x.hist=c(x.hist,x)
grad = 2*x+2
}
x.temp=seq(-10,10,0.1)
plot(x.temp, x.temp^2+2*x.temp,type='l',lwd=2)
lines(x.hist,x.hist^2+2*x.hist,type='o',pch=1,col='red',cex=1)
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