Data Carpentry for the Social Sciences with R
Date: 13 - 14 December 2018
Time: 10am - 4.30pm
Instructor: Peter Smyth
Fee:£390 (£280 for those from educational, government and charitable institutions).
CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.
Humanities PGR students at The University of Manchester can apply for a methods@manchester bursary to help cover their costs. All applications will be considered on a case-by-case basis and applicants will be required to provide a supporting statement from their supervisor.
Please contact Joshua Edgar (email: firstname.lastname@example.org) for an application form and further information.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
Data Carpentry workshops are for any researcher who has data they want to analyse, and no prior computational experience is required. This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data.
On completion of this course, the participants will be able to:
- understand problems which can occur in spreadsheets of data
- create ‘clean’ spreadsheets either from scratch or by reformatting a ‘dirty’ spreadsheet
- use OpenRefine to clean datasets and perform basic exploratory data analysis on the data
- use SQL to summarise data and to join different data sources
- use basic functionality in the R programming language to perform basic EDA (Exploratory Data Analysis) and to create a simple visualisation of data.
- convert data formats using R
- understand the importance of documenting work for future use.
- Wickham, Hadley (2014). “Tidy Data” Journal of Statistical Software, August 2014, Volume 59, Issue 10.
About the instructor
Peter Smyth is a Research Associate at The University of Manchester, based in the Cathie Marsh Institute. He has spent 35 years working in IT at various large and small commercial organisations before taking an MSc in Big Data Analytics at Sheffield Hallam University and moving into academia. In his previous roles, he used any convenient programming environment to hand to solve problems. Now he teaches a variety of programming languages to help others to do the same.
He is a qualified Data and Software Carpentry instructor.