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

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

# basic operations:
> 7+5
[1] 12
> 7-5
[1] 2
> 7*5
[1] 35
> 7/5
[1] 1.4

# use the function c() for creating a vector 
> c(1,2,3)
[1] 1 2 3
> c(1,2,3)+c(2,3,4)
[1] 3 5 7
> c(1,2,3)*2
[1] 2 4 6
> c(1,2,3)/2
[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
 [1] 72 70 71 66 73 66 72 72 74 75

> mean(height)              # compute sample average
[1] 71.1
> median(height)            # compute sample median
[1] 72
> mean(height, trim=0.1)    # trimmed mean.
[1] 71.25
> var(height)               # variance
[1] 9.211111
> sqrt(var(height))         # sd
[1] 3.034981
> height[2]                 # the second element of the vector
[1] 70
       
# generate a vector 
> rep(2,3)               # a vector of 2's of length 3
[1] 2 2 2
> seq(1,10, length=20)   # a vector of length 20, equally spaced entries
 [1]  1.000000  1.473684  1.947368  2.421053  2.894737  3.368421  3.842105
 [8]  4.315789  4.789474  5.263158  5.736842  6.210526  6.684211  7.157895
[15]  7.631579  8.105263  8.578947  9.052632  9.526316 10.000000

# Importing the data from a file, student.dat
# I have this file placed in C:/MyFiles/courses/368/data/student.dat
# The directory structure is mine; yours will be different and 
# so you will have to change the next line correspondingly
> student <- read.table("C:/MyFiles/courses/368/data/student.dat",header=T)
 
> attach(student)    # access each column of 'student'

# various histograms:
> hist(weight)
> hist(height)
> hist(lucky)
> hist(random)

> stem(lucky)    # stem&leaf for illustration

> mean(height)
> median(height)
> mean(height, trim=0.1)

> var(height)
> range(height) 

> summary(height)

> boxplot(height)
> boxplot(random)

> q()    # quit R
> help() # to get help