Advanced Statistical Analysis Using R: Online

The focus of this course is on learning advanced statistical methods using R.

 

This course is intended for those who have basic knowledge and experience with R, and would like to further advance or develop their experiences with advanced statistical methods in R. The course would also be suitable for people familiar with these statistical methods in other packages, but with no prior experience using R.

 

*This course will be run over 5 days in three sessions per day:

  • 10.00am - 11.30am - Session 1
  • 12.30am - 2.00pm - Session 2
  • 3.00 - 5.00pm - Session 3 exercises and consultation

 

Exercises will be provided and there will be opportunities for consultation with Mark in the afternoon sessions

 

This course is being held online via Zoom and run on Australian Eastern Daylight Time (UTC +11)

(Canberra, Sydney, Melbourne Daylight Savings time)

 

 
Level 3 - runs over 5 days
Course dates: Monday 6 February 2023 - Friday 10 February 2023
Instructor: 

Dr Mark Griffin is the Director of Insight Research Services Associated (www.insightrsa.com), where Insight consists of Insight Business Analytics, and Insight Training and Events. Insight Business Analytics providing training and consulting across the areas of business, statistics and IT. Insight Business Analytics is a Business Partner of Microsoft and a member of the IBM's Partner World and Google's Partner Program. Insight Training and Events teaches 30 qualifications from Certificate I to Graduate Diploma level across the areas of business, information technology, health and social services, and civil and environmental engineering.

 
Mark is also an Industry Fellow with the School of Business, University of Queensland, and has established and written training materials for several of their courses in Business Analytics. Mark serves on the Executive Committee for the Statistical Society of Australia, was the Co-Chair of their National Conference in 2021, and is the Founding Chair of their Section for Business Analytics. Mark is also the Founding Chair of the Business Analytics Special Interest Group within the International Institute of Business Analysis. To date he has presented over 100 two-day and 40 five-day workshops in statistics around Australia

Venue: 
Online
Week: 
Week 3
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.

 

The first day of this course will focus on the R software environment, the remaining days of this workshop will focus on learning advanced statistical methods with R.

 

We will spend an almost equal amount of time in PowerPoint sessions and computer exercises. During the PowerPoint sessions the focus will be on the statistical methods with minimal discussion of computer software. During the computer exercise time you will be using R to apply the statistical methods taught in the lectures.

At the start of each session of computer exercises Mark will perform the first exercise in each set on his own computer demonstrating to the class the use of the software and the statistical results obtained.

 

 

Course syllabus: 

Day 1

  • The R software environment:
    • what does the R window look like,
    • help screens in R,
    • data objects and data types in R,
    • importing and exporting data from R,
    • R packages,
    • writing your own R scripts,
    • data visualisation in R.
  • Introduction to linear Regression

 

Day 2

  • Regression diagnostics

  • Logistic and Poisson regression - Including odds ratios, incidence rate ratios

 

 

Day 3

  • Analysis of Variance
  • Factor analysis – including factor rotations, uniqueness and commonality

 

Day 4

  • Mixed effects models for longitudinal and clustered data.
  • Clustering techniques – k means clustering, cluster linkage, and dendrograms

 

Day 5

  • Missing data and multiple imputation

 

Course format: 

This course will run online via zoom.

You will need your own computer preloaded with R and an internet connection.

We will be in contact prior to the course to ensure you have the software you'll need.

 

As part of this course you will be using data from the Australian Data Archive (ADA). These datasets are restricted, so you will need to apply to the ADA for access as a prerequisite for the course. In the weeks leading up to the course, ACSPRI will contact you with detailed instructions on how to do this.

 

 

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).

Recommended Background: 

This course is intended for three different demographics

  • Participants who have a basic knowledge and experience with statistical methods in R, and would like to further develop this statistical expertise.
  • Participants who have completed a basic course on statistical methods in 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 how to use these methods in 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
Early bird Member: 
$1,750
Early bird Non Member: 
$3,380
Early bird full time student Member: 
$1,030
Member: 
$2,200
Non Member: 
$3,750
Full time student Member: 
$1,900
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.

 

Participant feedback: 

 

Outstanding sessions and content throughout. I'm very grateful to have his slides and exercises as a future methods resource.

 

I wanted to say how much I’ve enjoyed Mark's course and his teaching style

 

Mark is an expert in statistics and his approachability and patience enables me to clarify queries that I have been trying to clarify from published knowledge. He’s really excellent in using instruction to clarify complex concepts in statistics.

 

Made it easy to understand

 

I’m going to utilize the skill I learnt here in my every day job.

 

Mark provided a reasonable balanced of self-guided work with interactive lectures- it was very well paced!

 

Got a good introduction to some important techniques in R and how they can be used in real world settings.

 

Program: 
Summer Program 2023
Notes: 

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

These will be posted to your nominated 'shipping address' in advance.