Statistical Training Program

Excellent Graphics in R
28 Apr

Excellent Graphics in R

We weave in discussion of the principles of excellent graphics, whilst introducing the grammar of graphics underlying the ggplot2 package in R. We put five basic principles into action for visualising data. This starts with the quintessential plots for showing statistical distributions: histograms, box plots, density plots and others. Then we consider plots of relationships: the humble scatterplot, with many options for refinement.
Mixed Methods 3 - Visualising and communicating the logic of Mixed Methods research
18 Apr

Mixed Methods 3 - Visualising and communicating the logic of Mixed Methods research

This workshop explores different ways of visualising the strategy for a Mixed Methods study, which lies at the heart of most quant(itative) studies, and some types of qual(itative) analysis.
Formulating open-ended questions for interviews as part of Mixed Methods
17 Apr

Formulating open-ended questions for interviews as part of Mixed Methods

This workshop provides a practical guide to the formulation, wording and sequencing of open-ended questions (OEQs), in the context of a semi-structured interview, and as part of a mixed methods study.
Interviewing Skills as part of Mixed Methods
05 Apr

Interviewing Skills as part of Mixed Methods

This workshop helps develop a set of practical skills, most relevant to conducting semi-structured interviews, as part of a mixed methods study. It is also applicable to other kinds of interviews.
Mixed Methods 2 - Conceptual Frameworks for Designing Mixed Methods Research
31 Mar

Mixed Methods 2 - Conceptual Frameworks for Designing Mixed Methods Research

This workshop shows how conceptual frameworks act as anchoring tools to introduce clarity to early research design and research design communication.
Induction into Thinking with R
28 Mar

Induction into Thinking with R

This workshop introduces R statistical coding and anaysis. We begin with an introduction to the thinking required to interact with a programming environment, then address 20 basic commands in R; these cover using R like a calculator, a scientific calculator or a spreadsheet, then progress to using simple functions. We show you how to create and inspect objects in R and how to begin to interpret the error messages you may obtain.