Course dates

Starting date, Monday 14 Jan 2019
10am - 5pm | 5 days
Starting date, Monday 18 Feb 2019
10 am - 5 pm | 5 days
Starting date, Monday 8 Apr 2019
10am - 5pm | 5 days

Course overview

Learn how to process and analyse data using many of R's powerful functions, install packages for additional functionality and produce high quality graphics for use in publications.

Content was a great blend of statistics and programming. Fantastic course - Will is terrific!

I loved the course - the best I have experiences in 34 years in academia! Well structured and with excellent teachers who understood what beginners need.

This course offers an intensive, hands-on introduction to the R statistical computing environment, focusing on practical aspects of data analysis. The programme is designed to give you as much practical experience as possible.

The course will cover the following key aspects of using R:

  • Data analysis, reading in data, data exploration and filtering
  • Vectors, arithmetic, recycling
  • Graphics and advanced graphics
  • Analysis workflow
  • Making your own functions
  • Linear modelling
  • Object-orientated programming
  • Principal component analysis

You will experience a range of teaching and learning methods, including lectures, active participation in tutorials, practical sessions, debates and discussions. You will also receive academic guidance and feedback on your progress throughout.

By the end of this course, you will be able to read in a variety of structured and unstructured datasets. You will be able to ‘clean’ data, which contain errors or are badly entered, as well as re-structuring data to make it more useful to you. By the end of the course you will have applied both linear and non-linear models on a number of different datasets to help identify and quantify important relationships between variables. You will have created publication-quality visualisations that help express these relationships visually. In your final day task you will build a predictive model based on real data concerning either: the factors that predict survival on the titanic AND/OR the factors that predict childhood bullying. This task will involve real world datasets that will require data cleaning, visualisation as well as data modelling and will demonstrate your new ability to handle and gain insight from large and unfamiliar datasets.

Those interested in large-scale data analysis and in further programming training should consider Introduction to Python in Week 2. This combination will offer a competetive edge to anyone interested in analysing, managing and working with different types of data. 

Tutoring

The course is directed by Dr Will Lawrence, who completed his PhD at the department of Electronics and Computer Science at the University of Southampton, and who has a background in psychology. Will has rich experience in delivering training in both Python and R, to diverse audiences.

 

All AIR courses & About AIR

Fees

£750

Booking information

Discounts

  • 10% if you are taking two courses in consecutive weeks
  • 20% UK students
  • 25%Members of the UK Law and Society Association (UKLSA) 
  • If five people register from the same institution for the same intake, the fifth place is free
  • Goldsmiths students, staff and alumni - email us for current discounts

Refund policy: See AIR courses main page

Starting date, Monday 14 Jan 2019
10am - 5pm | 5 days
Starting date, Monday 18 Feb 2019
10 am - 5 pm | 5 days
Starting date, Monday 8 Apr 2019
10am - 5pm | 5 days

Enquiries

If you have any questions about this course please contact air (@gold.ac.uk) or call +44 (0)20 7078 5468.

For information on our upcoming short courses please sign up to our mailing list.

Location

14-18 Jan - Goldsmiths' Senate House venues, London, Bloomsbury, London

18-22 Feb - Goldsmiths' Main Campus, New Cross, London

8-12 Apr - Goldsmiths' Main Campus, New Cross, London

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