psyteachr_dsrr Ch. 09

select()

{dplyr}

keep specified columns

geom_hline()

{ggplot2}

plot horizontal reference line

return()

{base}

return value

names()

{base}

return (and can assign) column names

geom_smooth()

{ggplot2}

create smoothed lines to plot

read_csv()

{readr}

read comma delimited files

mutate()

{dplyr}

create or modify data columns

geom_point()

{ggplot2}

add layer of points to plot

as.numeric()

{base}

coerce object to numeric

rnorm()

{stats}

generate random sample from normal distribution

aes()

{ggplot2}

create aesthetic mappings between data and plot

c()

{base}

create vector of numbers, characters, etc.

filter()

{dplyr}

keep rows based on values of columns

runif()

{stats}

generate random number from uniform distribution

cor()

{stats}

compute the correlation of two vectors

mean()

{base}

calculate mean of elements of vector

scale_x_continuous()

{ggplot2}

scale x axis to be continuous

xlim()

{ggplot2}

specify limits of x axis

as_tibble()

{tibble}

coerce object into tibble

library()

{base}

load R packages

ggplot()

{ggplot2}

create a plotting area

sample()

{base}

randomly sample from vector

tibble()

{tibble}

create tibble

quantile()

{stats}

calculate sample quantiles

n()

{dplyr}

return current group size

t.test()

{stats}

computer one and two sample Student’s t-test on vectors of data

geom_vline()

{ggplot2}

plot vertical reference line

seq()

{base}

create sequences of numbers

matrix()

{base}

create matrix of numbers, characters, etc.

sd()

{stats}

compute standard deviation

list()

{base}

create recursive vector (list)

data.frame()

{base}

create data frame

geom_histogram()

{ggplot2}

create histogram of counts as bars

mvrnorm()

{MASS}

produce samples from multivariate normal distribution

map_dbl()

{purrr}

apply a function to multiple elements of an object in purrr, return a double vector

The end!