Statistics and Statistical Programming (Winter 2017)/R lecture outline: Week 4: Difference between revisions
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sort.list() | * keys stuff for building confidence intervals and p-values: | ||
complete.cases() | ** compute a sample standard error just like we did in the book, but in R | ||
** t.test() with one sample (build a confidence interval) | |||
* two things I showed in class which are super useful: | |||
** sort.list() | |||
** complete.cases() | |||
* doing something repeatedly: | |||
** just define a function and then apply it to a list of things | |||
** if you to output something in the middle: you use the print() function | |||
* doing simple simulations | |||
** runif() | |||
** rnorm() | |||
* running quick simulations | |||
** lets look at the relationship between mean and standard deviation on a 1 through 10 likert scale | |||
== Skipped for now == | == Skipped for now == | ||
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*** The “r” functions return random samples from a distribution. | *** The “r” functions return random samples from a distribution. | ||
**** runif(n=1, min=0, max=3) # a random value in [0,3] | **** runif(n=1, min=0, max=3) # a random value in [0,3] | ||
Revision as of 23:05, 25 January 2017
- keys stuff for building confidence intervals and p-values:
- compute a sample standard error just like we did in the book, but in R
- t.test() with one sample (build a confidence interval)
- two things I showed in class which are super useful:
- sort.list()
- complete.cases()
- doing something repeatedly:
- just define a function and then apply it to a list of things
- if you to output something in the middle: you use the print() function
- doing simple simulations
- runif()
- rnorm()
- running quick simulations
- lets look at the relationship between mean and standard deviation on a 1 through 10 likert scale
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]
- The “d” functions return the p.d.f. of the distribution
- distribution functions: lets focus on *unif(): the key is on page 222 of Verzani