<- Back to all events

R-Programming – Stage 2 (Intermediate)

R Programming – Stage 2 is the intermediate R Programming one (1) day short course for those who have completed R Programming – Stage 1 or for those who consider themselves to have a working knowledge of R.

In stage 2 of R Programming we will move forward to cover more of the visualisation and statistical methods in R. We will deal with larger datasets and will need to process them quite significantly when we import them. We will learn to use more advanced multivariate techniques for visualisation, and we’ll investigate interactive visualisations. We’ll also look at some more statistical techniques and will introduce concepts to do with analysing time-series data. Finally, we’ll look at some newer ways of iteratively developing analysis methods using the ‘chaining’ of data manipulation methods.

Who will benefit? This program is particularly useful for (audience)

Students undertaking a research program that requires data analysis skills
Researchers & Academics who wish to explore modern statistical languages
Industry Practitioners who wish to process data using R.

Program topics:

Iteratively developing analysis procedures in R
Reading data from online sources
Parsing data from untidy data files
Multivariate plotting for exploratory data analysis
Building interactive graphics for presenting data through web applications
Building interactive dashboard systems
Reformatting and reshaping data
Reproducible research
The ‘split-apply-combine’ strategy and other chaining strategies for data analysis
The ‘List’ data structure and its use in R.
Fitting statistical models
Introductory time-series statistical techniques.

Course outcomes:
Upon completion of this course, students will be able to:

Navigate and clean large data files.
Interactively explore and visualise datasets to answer questions.
Develop analysis procedures that scale to large datasets.

About the presenter:

Sam Ferguson is a Lecturer in the School of Software, Faculty of Engineering and IT at the University of Technology, Sydney. He has used R in a many of his approximately 35 publications in areas as diverse as spatial hearing and loudness research, to sonification, emotion, and tabletop computing. He has 10 years’ experience teaching programming and technical topics, and has taught numerous subjects at the postgraduate and undergraduate level at the University of Technology, Sydney, the University of Sydney and at UWS. He has been a research fellow or assistant on more than 6 ARC research projects (many of which used R as their primary data analysis language).

Additional information

Assessment within Short Course
Post Short Course follow up and engagement
Survey and feedback process
Online readings

Fees:

Full fee – $900.00 (GST free)
UTS Alumni and staff- 10% discount
2 or more from the one organisation – 15% discount
Interstate participant – 25% discount
Enrol in any 2 stages – 5% discount in addition to discount already eligible (upfront payment)
Enrol in all 3 stages – 10% discount in addition to discount already eligible (upfront payment)

Please select discount option with drop down box before entering your credit card details. Only 1 discount applicable per person.
Group bookings must be made individually with the 15% discount selected and credit card processed separately for each person.

Further Information
Venue Map

Contact Information:

For specific queries regarding course content, please contact Colin Wise, Advanced Analytics Institute Tel: +61 (02) 9514 9267 or email colin.wise@uts.edu.au with questions relating to this course

https://shortcourses-bookings.uts.edu.au/ClientView/Schedules/ScheduleDetail.aspx?ScheduleID=1933&EventID=1600

When

30th April 2015 09:00 am
To 30th April 2015 05:00 pm

Where

Sydney
UTS Short Courses Venue (AAI), Building 10, Level 7, Room 104, 235 Jones Street, Ultimo
Sydney 2007