Foundations of R for Research: Online - (2 days)

This 2-day workshop covers the foundations of using the free open-source R and RStudio programs to run their analysis. The course is a mix of lectures and hands-on exercises to introduce participants to the foundations for using R and RStudio.

 

This course will be offered online via Zoom And will run to the following timetable:

  • 9.30am -11.00am: Instructional Zoom session
  • 11.00am-11.30am: Break
  • 11.30am-12.30pm: Instructional Zoom session
  • 12:30pm-1.30pm: Lunch
  • 1.30pm-3.00pm: Instructional Zoom session
  • 3.00pm-3.30pm: Break
  • 3.30pm-4.30pm:  Exercises

 

Please note: Courses will run on Australian Eastern Daylight Time (UTC +11)

(Canberra, Sydney, Melbourne & Hobart Daylight savings time)

 

 

 
Workshop - runs over 2 days
Instructor: 

Dr Joanna Dipnall is an applied statistician with interests in the advanced statistical methods, including machine learning and deep learning techniques. She completed her Honours in Econometrics with Monash University and her PhD with IMPACT SRC, School of Medicine, Deakin University. Joanna works extensively with registry and linked medical data and collaborates extensively with the Faculty of IT at Monash to supervise Masters and PhD students to integrate artificial intelligence within health research. Joanna teaches within the Monash Biostatistics Unit and is the Unit Co-coordinator for the Monash Masters of Health Data Analytics course. Joanna has taught advanced statistical methods for many years at universities and for ACSPRI.

Course dates: Friday 15 October 2021 - Saturday 16 October 2021
Course status: Course completed (no new applicants)
Venue: 
Online
Week: 
Week 1
About this course: 

This course is a step by step interactive introduction for participants with no experience with R and RStudio. Notes will be provided and a set of exercises, covering a variety of data sets, will be run together during the lecture and also individually at the end of the day. The course content is particularly suited for those involved in research in the business, education, social and health sciences.

 

Participants will first be introduced to the foundations of R such as libraries, matrix manipulation, objects, and data frames. Participants will use R Markdown in RStudio to generate reports, tables and graphics to Word, PDF and HTML files. Once the foundations have been covered a variety of data management skills will introduced (e.g. filtering data, merging data). The production of descriptive statistics tables and graphs will be covered so that participants can easily use RStudio to explore data and produce reports.

 

The last session on each day will finish with a set of exercises for participants to run on their own and practice what they have learned that day. Please note that due to the short 2-day structure, there will not be any time set aside for analysing participant’s own data.

 

Course syllabus: 

Day 1

  • Lecture 1: Foundations of R
  • Lecture 2: Foundation data management skills
  • Lecture 3: Producing basic statistics and tables
  • Lecture 4: Producing your first simple report
  • Exercises in R

 

Day 2: 

  • Lecture 1: Review of day 1
  • Lecture 2: Extending data management skills
  • Lecture 3: Basic R Graphics
  • Exercises in R

 

Course format: 

This workshop will take place 'live' online using zoom.

Participants are required to use their own laptop and have downloaded R and RStudio prior to the workshop

Recommended Background: 

This course assumes that participants have:

(1) A reasonable understanding of statistics to be able to comprehend the basic statistics such as mean, median and interquartile range.

(2) Some familiarity with a PC environment including keyboard skills and understanding of folder and file structures.

(3) Some experience in using Microsoft Word and Excel or their equivalent.

It does not assume prior experience with R, Stata, SAS, SPSS or any other specific statistical packages although any such experience would be helpful.

Recommended Texts: 

Course notes will be supplied.

 

No specific references are suggested but participants might find the following text useful:

  • “Discovering Statistics Using R” by Andy Field and Jeremy Miles.
  • “Data Analysis and Graphics Using R” by John Maindonald and W. John Braun.
Course fees
Member: 
$1,480
Non Member: 
$2,280
Full time student Member: 
$1,280
Participant feedback: 

 

The workshop was focused heavily on applying the skills Jo taught us through R and R studio which made it a valuable course. (Nov 2019)

 

ˆ I had never used R prior to this course, so its set me off on the right foot. (Nov 2019)

 

I obtained basic understanding of R which is what I was looking for. (Nov 2019)

 

Supported by: