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Statistics LibreTexts

Appendix D: Most essential R commands

  • Page ID
    3623
  • This is the short collection of the most frequently used R commands based on the analysis of almost 500 scripts (Figure 3.4.2). For the longer list, check R reference card attached to this book, or R help and manuals.

    ?

    Help

    <-

    Assign right to left

    [

    Select part of object

    $

    Call list element by name

    abline()

    Add the line from linear regression model

    aov()

    Analysis of variation

    as.character()

    Convert to text

    as.numeric()

    Convert to number

    as.matrix()

    Convert to matrix

    boxplot()

    Boxplot

    c()

    Join into vector

    cbind()

    Join columns into matrix

    chisq.test()

    Chi-squared test

    cor()

    Correlation of multiple variables

    colSums()

    Sum every column

    cor.test()

    Correlation test

    data.frame()

    Make data frame

    dev.off()

    Close current graphic device

    dotchart()

    Replacement for “pie” chart

    example()

    Call example of command

    factor()

    Convert to factor, modify factor

    file.show()

    Show file from disk

    function() ...

    Make new function

    head()

    Show first rows of data frame

    help()

    Help

    hist()

    Histogram

    ifelse()

    Vectorized condition

    legend()

    Add legend to the plot

    library()

    Load the installed package

    length()

    Length (number of items) of variable

    list()

    Make list object

    lines()

    Add lines to the plot

    lm()

    Linear model

    log()

    Natural logarithm

    log10()

    Decimal logarithm

    max()

    Maximal value

    mean()

    Mean

    median()

    Median

    min()

    Minimal value

    NA

    Missed value

    na.omit

    Skip missing values

    names()

    Show names of elements

    nrow()

    How many rows?

    order()

    Create order of objects

    paste()

    Concatenate two strings

    par()

    Set graphic parameters

    pdf()

    Open PDF device

    plot()

    Graph

    points()

    Add points (dots) to the plot

    predict()

    Predict values

    q("no")

    Quit R and do not save workspace

    qqnorm(); qqline()

    Visual check for the normality

    rbind()

    Join into matrix by rows

    read.table()

    Read data file from disk into R

    rep()

    Repeat

    sample()

    Random selection

    savehistory()

    Save history of commands (does not work under macOS GUI)

    scale()

    Make all variables comparable

    sd()

    Standard deviation

    source()

    Run script

    str()

    Structure of object

    summary()

    Explain the object, e.g., return main description statistics

    t()

    Transpose matrix (rotate on right angle)

    t.test()

    Student test (t-test)

    table()

    Make contingency table

    text()

    Add text to the plot

    url.show()

    Show the Internet file

    wilcox.test()

    Wilcoxon test

    write.table()

    Write to disk