# Use the method runif (random-uniform) to select 
# 100 numbers randomly distributed betweeen 0 and 1 
my_rands<-runif(100,0,1)
my_rands
# get some of the statistical results on this vector
mean(my_rands)
sd(my_rands)
median(my_rands)
quantile(my_rands,0.25)
quantile(my_rands,0.75)

# we might use these numbers to simulate the flipping 
# of a coin -- heads if number > 0.5 tails otherwise
coins<-ifelse(my_rands>=0.5,"H","T")
coins
# another way to simulate 100 coin tosses is to use the 
# sample method
outcomes<-c("H", "T")
coins2<-sample(outcomes,100, replace=TRUE)
coins2
# A quick way to achieve a count of each outcome 
# the so-called frequencies is to use the table methd
table(coins2)
# the difference between replace=TRUE and replace=FALSE 
# can be understood if we having the program pick  
# lottery numbers 
# in PICK5 (www.palottery.state.pa.us) one picks 5 
# numbers from 0-9 duplications are allowed
sample(0:9, 5, replace=TRUE)
# in CASH5 one picks 5 unique numbers from 1 to 43 
sample(1:43, 5, replace=FALSE)
# to simulate the rolling of 100 dice
# and find the frequencies 
dice = sample(1:6, 100, replace=TRUE)
table(dice)
hist(dice)
hist(dice, breaks=0.5:6.5)