###############
## R WARM-UP ##
###############

### READ IN DATA FROM A COMMA-SEPARATED VALUES FILE
### DOWNLOAD FROM http://people.ucsc.edu/~mwagers/ling280/data/plurals.csv.gz

> .... -> plurals
summary(plurals)

### EXTRACT THE RTs 
> .... -> rt.plurals
summary(rt.plurals)

### CONSTRUCT A HISTOGRAM WITH 25 ms BINS
> .... 

### INSTALL SOME NEW TOOLS
install.packages("psych")
require(psych)

### CREATE A NEW TOOL
multiplot<-function(row,col) {
	par(mfrow = c(row,col),pty="s")
	par(mar=c(3,3,3,2))
}

### SIMULATE SOME COIN FLIPS
rbinom(1500,4000,0.75)->coin.flips

###
multiplot(2,2)

hist(rt.plurals,breaks=seq(0,4000,50),main="RTs",freq=FALSE,xlim=c(0,2000))
hist(coin.flips,breaks=40,main="Coin flips",freq=FALSE)
hist(-rt.plurals,breaks=seq(-4000,0,50),freq=FALSE,xlim=c(-2000,0))

#### WHAT IS BEING QUANTIFIED HERE?

skew(rt.plurals)
skew(coin.flips)
skew(-rt.plurals)


######################
## BINOMIAL WRAP-UP ##
######################

### SUPPOSE THE LIKELIHOOD OF HEADS IS GIVEN BY p = 0.75
### What is the choice of the head count being 20 for a 40-coin flip?

> .... 

### p = 0.75, 40 events, likelihood of count being 30

> ....

### p = 0.75, 4 events, likelihood of count being 3

> ....

### p = 0.75, 400 events, likelihood of count being 300

> ....

### INTERVALS/RANGES

n.events <- 40
p.event <- 0.7

sim.events<- rbinom(10000, 40, 0.7)

probs <- dbinom(0:n.events, n.events, p.event)

plot(0:40, probs, col="red", lwd=3, pty='l')
hist(sim.events, breaks=0:40, freq=FALSE, col="grey", density=20, add=1)

abline( v = mean(sim.events) )

###

###  +/- 1
sum(probs[28:30])
abline( v = c(27, 29), col="blue",lwd=2) 
# remembers probs[1] corresponds to 0 heads

###  +/- 2
sum(probs[27:31])
abline( v = c(26, 30), col="green", lwd=2) 

###  +/- 6
sum(probs[23:35])	
abline( v = c(25, 31), col="purple", lwd=2)