rm(list = ls())  # clear the memory
###########################

# This is a brief introduction to R
# Open R, and then work through these commands

#   '#'  = comment
#   '<-' or '=' = affect; defines the left hand side to be the right hand side
#   '>'  = prompt of R

# basic operations - enter these; see what you get: 

7+5

7-5

7*5

7/5

7/0

0/0

# use the function c() for creating a vector 
x = c(1,2,3) 
x  # response: [1] 1 2 3
x = 1:3 # Gives the same thing
x

x = c(1,2,3) + c(2,3,4) 
x # response: [1] 3 5 7

c(1,2,3)*c(2,3,4) # response: [1]  2  6 12

c(1,2,3)*2 # response: [1] 2 4 6

c(1,2,3)/2 # response: [1] 0.5 1.0 1.5

# create a vector, called 'height', containing 10 values
height <- c(72,70,71,66,73,66,72,72,74,75)
height # response: [1] 72 70 71 66 73 66 72 72 74 75

mean(height)              # compute sample average

median(height)            # compute sample median

mean(height, trim=0.1)    # trimmed mean.

var(height)               # variance
sum((height - mean(height))^2)/(length(height)-1)
				# should give the same thing - why?

sqrt(var(height))         # standard deviation

height[2]                 # the second element of the vector

       
# generate a vector 
rep(2,3)               # a vector of 2's of length 3: [1] 2 2 2

seq(1,10, length=21)   # a vector of length 21; equally spaced entries spanning [1,10]


##############################################
# Go to http://www.stat.ualberta.ca/~wiens/stat568/stat568.html and download the data sets which are there.
# Then to use these files without going to the web, replace lines like
# read.table("http://www.stat.ualberta.ca/~wiens/stat568/datasets/xxx.dat") 
# with lines leading to where the data sets are on YOUR system. (Note that FORWARD slashes are required.)
# You can specify the directory from which R starts - right click on the R icon and go to 'Properties'.

help(read.table)
pulp = read.table("http://www.stat.ualberta.ca/~wiens/stat568/datasets/pulp_Table_2_1.dat", header = T, quote= "")
pulp
# You can specify the directory from which R starts - right click on the R icon and go to 'Properties'.

colnames(pulp)
colMeans(pulp) # Means of the four columns

apply(pulp, 2, var)  # Apply the 'variance' function to each column of 'pulp'

# Plotting:
pairs(pulp)


# For a more sophisticated plot, click on Packages on the top menu of the screen, 
# choose a mirror (e.g. in BC) and install the "cars" package - it contains the scatterplotMatrix function
library(car)
dev.new()
scatterplotMatrix(pulp, diagonal = "boxplot", ellipse = TRUE)

##############################################
# Using 'scripts':  What you are reading right now is an example of a 'script' - a list of commands
# to be carried out by R.  In your work you will typically have a script for each assigned question, etc.
# To open a blank script, click on File -> New script in the R menu at the top of the screen.
# To save the script for future use, click on the 'save' icon and follow the instructions.
# To run the command in the script, save it and then click on Edit -> Run all.  
# (Try it - to run THIS script, save it to a directory somewhere, then re-open it and run it.)
# Alternatively, one will often just copy and paste a few commands, from the script, 
# into the Command window ("R console") in order to try them out.