Statistics and Statistical Programming (Winter 2017)/R lecture outline: Week 3

Review of material from class

 * loading data:
 * load versus read.csv
 * when things don't coopreate...
 * library(foreign)
 * defining functions
 * syntax for defining functions: show the my.mean function
 * calling functions (your own or others) with apply, lapply, sapply
 * stuff related to distributions
 * rep
 * seq
 * sample; and sampling into data.frames

Online only

 * dates with POSIXct. dates will almost always be given to you as characters, and you need to parse them
 * tapply, and putting things back into data.frames
 * merge

Skipped for now

 * ordered — really just a type of factor for ordinal data


 * distribution functions: lets focus on *unif: the key is on page 222 of Verzani
 * The “d” functions return the p.d.f. of the distribution
 * dunif(x=1, min=0, max=3) # 1/3 of the area is the to the left 1
 * The “p” functions return the c.d.f. of the distribution.
 * dunif(q=2, min=0, max=3) #1/(b-a) is 2/3
 * The “q” functions return the quantiles.
 * qunif(p=0.5, min=0, max=3) # half way between 0 and 3
 * The “r” functions return random samples from a distribution.
 * runif(n=1, min=0, max=3) # a random value in [0,3]
 * running quick simulations
 * lets look at the relationship between mean and standard deviation on a 1 through 10 likert scale