In this class we’ll use the software called R inside another software called RStudio that provides a great graphical and intuitive user interface.

R is the name of the software itself, but also the name of the programming language that is used within the software.

Just like a cooking recipe is a series of tasks to prepare a dish starting with specific ingredients, a program is simply a list of instructions to be performed and the ingredients are the data that are provided within a dataset.

The instructions are written with a programming language, in our case R.

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This 5 minutes video R - Coding - 4.1[^R_coding_4.1] explains how R is useful in data science. [^R_coding_4.1]:https://youtu.be/xp1l7utYFGs.

Students should install the following two software on their computer.

Both R and RStudio have versions for the three main types of computers.

Once installed, working within the software is the same on all computer platforms.

Choose the version for your computer and follow installation instructions.

The installation process is rather intuitive.

If you need more guidance the following step-by-step videos would be useful:

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Installing R and RStudio on Windows 10 (March 20, 2020 - 3min 23sec).

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• Installing R and Rstudio on macOS (Mar 22, 2020 - 4min).

Packages are modular additions to the R software that add functionality in the form of new functions, included datasets, documentation, etc.

The standard repository of R packages The “Comprehensive R Archive Network” (CRAN) will likely be the most used for environmental health.

Adding packages is like adding gears for a more powerful engine.

One of a “suite” of packages that we’ll use is called Tidyverse and it should preferably be installed before classes start.

While Tidyverse is a suite of multiple packages, this can be installed just like a single package with that single name.

The method to add a package is rather simple: Copy the following command in the R console:

install.packages("tidyverse")

Alternatively use the Packages pane in RStudio to do the installation with the graphical interface. To install in RStudio follow this video Installing Packages in R Studio (Nov 20, 2012 - 2.52 min) and use the package name Tidyverse instead.

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To install in R follow the demonstration in the video How to Install Packages in R (Aug 9, 2013 - 6:24min).

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Exercises in this book will be from the National Health and Nutrition Examination Survey (NHANES)¹ a survey research program conducted by the National Center for Health Statistics (NCHS)² to assess the health and nutritional status of adults and children in the United States, and to track changes over time.

An article in FAQS.org (Beals (2008)) details the history of NHANES and how the collected data is used.

NHANES logo.

NHANES data is collected in datasets and we’ll use datasets from the 2 year collection between 2015 and 2016.

Video³: How are the data collected from the participant’s point of view NHANES Participants (English) 2:22min.

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See also⁴: The Latest Data Release and Reports from the National Health and Nutrition Examination Survey May 21, 2020 - 57:29 min.

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A number of small datasets are included with R during installation.

We might make use of one or more.

There is no further installation required to access the included datasets.