Using R for Advanced Statistical Analysis

This course is intended for those who have basic knowledge and experience with R, and would like to further advance or develop their experiences in R and advanced statistical methods. The course would also be suitable for people familiar with these methods in other packages, but wanting to learn R for the first time.

 
Level 3 - runs over 5 days
Instructor: 

Dr Mark Griffin is the Founding Director of the Australian Development Agency for Statistics and Information Systems (www.adasis-oz.com), and holds an Adjunct appointment within the School of Public Health, University of Queensland. Mark serves on the Executive Committee for the Statistical Society of Australia, and is the Asia-Pacific Deputy Regional Director for the International Institute of Business Analysis. He has been the primary statistician and survey methodologist for a 6000-household survey exploring human trafficking in Cambodia, China, Laos, Myanmar, Thailand and Vietnam, and for a survey of 20,000 households exploring human trafficking in Sri Lanka. He is currently leading program evaluation teams for the Queensland Department of Communities, Child Safety, and Disability Services. To date he has presented over 80 two-day workshops in statistics around Australia.

Course dates: Monday 3 July 2017 - Friday 7 July 2017
Week: 
Week 2
About this course: 

R is a free software environment for scientific and statistical computing and graphics that runs on all common computing platforms. An active and highly skilled developer community works on development and improvement. It has become an environment of choice for the implementation of new methodology. It is at the same time attracting wide attention from statistical application area specialists. The powerful and innovative graphics abilities available in R include the provision of well-designed publication-quality plots.

 

Course syllabus: 

Day 1

Linear, logistic and Poisson regression - Including odds ratios, incidence rate ratios, and regression diagnostics

 

Day 2

Analysis of Variance

Factor analysis – including factor rotations, uniqueness and commonality

 

Day 3

Longitudinal data analysis - mixed effects models and generalized estimating equations

 

Day 4

Clustering techniques – k means clustering, cluster linkage, and dendrograms

Missing data and multiple imputation

 

Day 5

Data visualization – including radial plots, clustered and stacked bar charts, and donut plots. This will focus on ggplot and Rshiny.

 

Course format: 

Approximately half of the time in this workshop will be spent in PowerPoint seminars, and the other half will be spent in computer demonstrations and self-paced computer exercises (using datasets publicly available within R).

 

This course will either take place in a lab or you may have to bring your own laptop. You will be notified in advance.

Recommended Background: 

This course is intended for three different demographics

  • Participants who have a basic knowledge and experience with R, and would like to further develop this expertise
  • Participants who have completed a basic course on R with ACSPRI, and would like to take their skills to the next level
  • Participants who have some familiarity with these statistical methods in other software (eg SPSS, SAS or Stata), and who wish to learn the R system (potentially as new R users).

 

A basic knowledge of statistics is assumed. No prior knowledge of the statistical methods taught in this course or any prior experience with R is assumed, though students with prior knowledge will be better suited to tackle the more advanced topics in this workshop.

 

Participants must be comfortable with typing commands at the command line.

 

Recommended Texts: 

Maindonald, J.H. and Braun, W.J. (2010). Data Analysis and Graphics Using R. An Example-Based Approach. 3rd edn, Cambridge University Press.

 

Course Fees:
All courses at a given program have the same fee structure, but fees vary depending on whether your organisation is an ACSPRI Member and whether there are Early Bird Discounts available at the time. The prices for this program are available on the program page.
FAQ: 

Q: Do I have to have any prerequisites to do this course?

A: Yes see recommended background section.

 

Q: Is R really free and publicly available?

A: For sure. R has been / is being developed by an online community of statisticians and programmers around the world that have made all of their work available for the benefit of users.

 

Q: Can I download and install R prior to the workshop?

A: Yes, please visit https://cran.r-project.org. It is assumed that most if not all participants will not have installed R prior to the workshop, though there may be a couple of eager participants who want to make a head start.

 

Program: 
Winter Program 2017
Notes: 

The instructor's bound, book length course notes will serve as the course texts.