Statistics and Statistical Programming (Winter 2017)/R lecture outline: Week 3: Difference between revisions
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* loading data: | |||
** load() versus read.csv() | |||
** when things don't coopreate... | |||
** library(foreign) | |||
* defining functions | |||
** 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]
- The “d” functions return the p.d.f. of the distribution
- running quick simulations
- lets look at the relationship between mean and standard deviation on a 1 through 10 likert scale