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

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* problems folks ran into:
* loading data:
** loading data:
** load() versus read.csv()
*** load() versus read.csv()
** when things don't coopreate...
*** when things don't coopreate...
** library(foreign)  
*** library(foreign)  
* defining functions
* other things that have come up
** dates with POSIXct(). dates will almost always be given to you as characters, and you need to parse them
** ordered() — really just a type of factor for ordinal data
* new things that are going to be very useful
** defining functions
** merge()
* looping
** apply(), lapply(), sapply()
** apply(), lapply(), sapply()
** for looping
** for looping
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** rep()
** rep()
** seq()
** seq()
** sample()
** sample(); and sampling into data.frames
 
Online supplement:
 
* other things that have come up
** dates with POSIXct(). dates will almost always be given to you as characters, and you need to parse them
** ordered() — really just a type of factor for ordinal data
** merge()
 
 
Skipped for now:
 
** merge()
** distribution functions: lets focus on *unif(): the key is on page 222 of Verzani
** 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
*** The “d” functions return the p.d.f. of the distribution

Revision as of 19:58, 19 January 2017

  • loading data:
    • load() versus read.csv()
    • when things don't coopreate...
    • library(foreign)
  • defining functions
    • apply(), lapply(), sapply()
    • for looping
  • stuff related to distributions
    • rep()
    • seq()
    • sample(); and sampling into data.frames

Online supplement:

  • other things that have come up
    • dates with POSIXct(). dates will almost always be given to you as characters, and you need to parse them
    • ordered() — really just a type of factor for ordinal data
    • merge()


Skipped for now:

    • merge()
    • 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