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adventr: R tutorials for An Adventure in Statistics (Field, 2016)

The adventr package contains a series of interactive tutorials that teach R alongside chapters of my 2016 textbook An Adventure in Statistics: the reality enigma. The tutorials are written using a package called learnr. Once a tutorial is running it's a bit like reading a book but with places where you can practice the R code that you have just been taught. The adventr package is free (as are all things R-related) and offered to support tutors and students using my textbook who want to learn R.

Contents of adventr

The package was written initially to support my own teaching on a module where I base the content around An Adventure in Statistics. One quirk of this is that there are some advanced tutorials on topics not covered in the book (but continue the themes of the book ...). Another quirk is that - at present - there are some chapters that don't have associated tutorials (for example, the Chapter on probability).

The tutorials are named to correspond (roughly) to the relevant chapter of the book. For example, adventr_03 would be a good tutorial to run alongside teaching related to chapter 3, and so on.

  • adventr_02: Data basics in R and RStudio
  • adventr_03: Summarizing data (introducing ggplot2)
  • adventr_04: Fitting models (central tendency)
  • adventr_05: Presenting data (summarizing groups and more ggplot2)
  • adventr_08: Inferential statistics and robust estimation (covers Chapter 9 too)
  • adventr_11: Hypothesis testing
  • adventr_14: The general linear model
  • adventr_15: Comparing two means
  • adventr_15_rm: Comparing two means (repeated measures)
  • adventr_16: Comparing several means
  • adventr_16_rm: Comparing several means (repeated measures)
  • adventr_17: Factorial designs
  • adventr_mlm: Multilevel models (not covered in the book)
  • adventr_growth: Growth models (not covered in the book)
  • adventr_log: Logistic regression (not covered in the book)

Running tutorials

To run a particular tutorial execute:

library(adventr)
learnr::run_tutorial("name_of_tutorial", package = "adventr")

and replace "name of tutorial" with the name of the tutorial you want to run. For example, to run tutorial 3 (for Chapter 3) execute:

learnr::run_tutorial("adventr_03", package = "adventr")

The name of each tutorial is in bold in the list above. Once the command to run the tutorial is executed it will spring to life in a web browser.

Suggested workflow

The tutorials are self-contained (you practice code in code boxes) so you don't need to use RStudio at the same time. However, to get the most from them I would recommend that you open two RStudio sessions (i.e. two RStudio windows running simultaneously). Use one RStudio session to run the tutorial. You won't then be able to use this RStudio window (because its resources are allocated to the tutorial). In the second RStudio session try replicating what you learn in the tutorial. That is, open a new script file and everything you do in the tutorial, practice in the script file (and save it). This workflow has the advantage of not just teaching you the code that you need to do certain things, but also provides practice in using RStudio itself.

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Version

Install

install.packages('adventr')

Monthly Downloads

271

Version

0.1.8

License

GPL-3

Maintainer

Andy Field

Last Published

May 5th, 2020

Functions in adventr (0.1.8)

calcite_dat

Calcite mask data
rehab_dat

Zombie rehabilitation data
adventr

adventr: tutorials in R for An Adventure in Statistics (Field, 2016).
jig_dat

JIG:SAW employee data.
mask_dat

Invisibility paste data
taser_dat

Zombie immobility data
ras_dat

Alice's RAS scores
alice_dat

Alice's gene data
memory_dat

Memory erasing data
rehab_growth_dat

Zombie rehabilitation longitudinal data
mem_cov_dat

Memory erasing data with covariate
recovery_dat

Zombie recovery data
teddy_dat

Teddy therapy data.
ha_dat

Subset of Ha et al. (2010) data
implant_dat

Memory implanting data
zhang_female_dat

Subset of Zhang data (female sample N = 20)
garlic_dat

Zombie garlic data