A series of brief instructional videos for developing foundational skills in the use of the R statistical computing and graphics software

This guide will provide you with access to instruction in the basic functionality of the R software for statistical computing and graphics.

Instruction is provided through a series of videos, which are listed below (see * Instructional Videos*) in the recommended order for viewing. If you already have some background in the use of R, you may skip ahead to a particular video of interest. However, since the successive videos build upon the content of earlier videos, it will be advantageous to view the videos in the order in which they are presented.

The videos contain a wide variety of examples demonstrating the use of R. These utilize data sets and pre-prepared code samples, which viewers may access and download by clicking on the * Supporting Content* tab on the left side of this page. To gain the full possible benefit from the videos, viewers are encouraged to download the supporting content and go through the examples on their own as they view the videos.

- Intro to R No. 01: OverviewDescription of the contents to be covered in the videos of the "Intro to R" series.
- Intro to R No. 02: What is R and why should you use it?A general description of R and the benefits of using it.
- Intro to R No. 03: Where do I get and install R and RStudio?Explains how to install R and its RStudio front end.
- Intro to R No. 04: Resources for Learning RWays to learn R, including both resources in the collections of Florida Tech's Evans Library and online resources available to the public at large.
- Intro to R No. 05: Basic R ComponentsDiscusses some of the more popular data modes handled by R, including numerical, integral, complex, logical and character data.

Describes the types of data objects encountered in R, including vectors, matrices, lists and data frames.

Lists common data file formats that may be imported into R. - Intro to R No. 06: Functions and PackagesThe structure of R commands, case sensitivity, the organization of commands with related purposes within packages, and the use of commands to create new data objects.
- Intro to R No. 07: Specifying Locations of Data ElementsSyntax for specifying desired data elements within R data objects.
- Intro to R No. 08: Starting up and configuring RStudioHow to start and configure RStudio.

Explanation of the uses of the different panes (windows) within RStudio. - Intro to R No. 09: Setting up your Working Directory in RStudioHow to set up your working directory in RStudio
- Intro to R No. 10: Installing & Activating R Packages in RStudioIndicates the R packages needed in the video examples.

Explains how to install and activate packages in RStudio. - Intro to R No. 11: Creating Data ObjectsHands-on examples of how to create data objects in R, including vectors, data frames, and matrices,

Discusses ways in which RStudio maintains records of previously created data objects and previously executed commands

Explains ways to access previously executed commands for the purpose of either reusing or modifying them.

Commands introduced include: "c", "data.frame", "matrix", and "View" - Intro to R No. 12: Accessing Built-in and External Data SetsProvides examples of how to access built-in data sets (i.e. those that are automatically installed with R), as well as how to upload external data sets (e.g. CSV files) using the RStudio interface..

Commands introduced include "data" and "?". - Intro to R No. 13: Specifying Elements, Rows and Columns in R Data ObjectsHands-on examples of syntax for specifying the exact data you need within R Data Objects.

Commands introduced include: "colnames" and "rownames" - Intro to R No.14: Inspecting Data ObjectsHands-on examples of methods for quickly establishing the contents and characteristics of R data objects.

Commands introduced include "head", "tail", "any", "all", "unique", "mean", "range", and "max". - Intro to R No. 15: Popular Mathematical Functions in RHands-on examples of commonly used mathematical functions, such as taking absolute values and square roots, as well as ways of rounding numbers based upon decimal places or significant values.

Commands introduced include: "abs", "sqrt", "ceiling", "floor", "trunc", "round", and "signif". - Intro to R No. 16: Substituting, Ordering, Aggregating and Taking Subsets of DataHands-on examples of how to identify and correct incorrect "dirry" data, as well as how to order data objects by specified fields, aggregate data, and take subsets of data objects.

Commands introduced include: "sub", "order", "aggregate", and "subset". - Intro to R No. 17: Exporting Data from RHands-on example of how to export an R data object to a CSV file.

Commands introduced include: "write.csv" and "write.table". - Intro to R No. 18: Performing Statistical Analysis in RCommonly used R statistical analysis tools.

Commands introduced include: "summary", "quantile", "seq", "library", "t.test", and "cor.test". - Intro to R No. 19: Quick Plots in RHow to do simple data plots in R, including scatter plots, arrays of plots, and box plots, as well as how to export plots as PDF or image files.

Commands introduced include: "dev.off", "plot", and "boxplot". - Intro to R No. 20: Creating an Elaborate Plotinstruction on how to prepare an elaborate plot using R, including formatting of background and label colors, labeling, tick marks, legends, trend lines, grid lines, etc.

Commands introduced include: "par", "points", "legend", "lm", "abline", "text", and "grid". - Intro to R No. 21: Quick Text FunctionsIntroduces some basic text functions, such as taking substrings, splitting text strings, and determining string lengths.

Commands introduced include: "substr", "nchar", and "strsplit". - Intro to R No. 22: Working with Dates and TimeConverting text fields into date format in R.

Commands introduced include: "as.Date"

- Last Updated: Oct 27, 2022 3:32 PM
- URL: https://libguides.lib.fit.edu/R_Tutorials
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