General Information

Introduction to R for non-programmers.

The goal of this workshop is to teach novice programmers to use R for data analysis. R is a programming language specifically designed for statistical analysis, is free and open source and is known for its array of third-party packages. It is thus commonly used in many scientific disciplines for data analysis. The emphasis of these materials is to give attendees without programming experience a strong foundation in the fundamentals of R, and to teach them how to use the packages from Tidyverse to import, manipulate and visualise data. What will be covered:

• Basics of R and R/Studio
• How to import data into R
• How to manipulate data
• How to make graphs using ggplot2

We will NOT be covering conditionals (if statements), for loops and writing functions.

Note that this workshop will focus on teaching the fundamentals of the programming language R, and will not teach statistical analysis. If you would like help with your statistical analysis, you can contact the Statistical Consulting Centre for one-on-one consultations or see their flyer for details of statistical training courses.

A variety of third party packages are used throughout this workshop. These are not necessarily the best, nor are they comprehensive, but they are packages we find useful, and have been chosen primarily for their usability. These materials are a modified version of those used by Software Carpentry for their "R for reproducible scientific analysis" workshop: Greg Wilson: "Software Carpentry: Lessons Learned". F1000Research, 2016, 3:62 (doi: 10.12688/f1000research.3-62.v2).

Who: The course is aimed at graduate students and other researchers. You don't need to have any previous knowledge of the tools that will be presented at the workshop. However, if you have no previous programming experience, we recommend that you consult the course material at introduction to programming concepts workshop prior to attending the current workshop.

Where: COLAB (Room 329), Level 3, ERC, Building 171, University of Melbourne, Parkville. Get directions with Google Maps.

Requirements: **Participants must bring a laptop and charger** with a Mac, Linux, or Windows operating sytem (not a tablet, Chromebook, etc.) that they have administrative privileges on.

Participants are also asked to install R, and the RStudio IDE prior to the workshop (details below).

Contact: Please email lucy.resbaz@gmail.com for more information.

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Schedule

Surveys

Please be sure to complete these surveys at the end of the workshop.

Survey

Other Resources

• Course notes

Google Doc: https://docs.google.com/document/d/1xbejPvcgVrm66zSwC0iwVg35Estxp0qf5Q3EMtX4DF8/edit?usp=sharing.
We will use this shared Google Doc for chatting, taking notes, and sharing URLs and bits of code.

Setup

Requirements: **Participants will be required to bring their own laptop and charger**

Wifi: If you're bringing a wifi device to the workshop, access to the wifi network will depend on whether you're affiliated with the Univerity of Melbourne. University of Melbourne staff/students can connect to the UniWireless network; instructions on how to do this and where to get assistance can be found here.

For visitors who are not from a tertiary institution, the visitor login details for the Software Carpentry network are:

• network: Software Carpentry
• password: hackerwithin