Data Analysis

This cluster introduces a range of technological tools, methods and approaches to qualitative and quantitative data analysis. There is also a new focus on statistical analysis.
28/10/2015 2.15pm-5.00pm CH1007 Introduction to SPSS Dr Alun Owen
18/11/2015 2.15pm-5.00pm CH1001 Introduction to Statistical Methods Dr Alun Owen
09/12/2015 2.15pm-5.00pm CH1001 Chi-Squared Dr Alun Owen
27/01/2016 2.15pm-5.00pm CH1001 T-tests Dr Alun Owen
16/02/2016 2.15pm-5.00pm EEG031 One Factor ANOVA Dr Alun Owen
17/02/2016 1.15pm-4.15pm CH1007 Introduction to NVivo Heather Yemm
05/04/2016 12.15pm-3.00pm EE1101 Non Parametric tests Dr Alun Owen
28/04/2016 1.00pm-5.00pm CH1001 Basic R Dr Roy Bhakta

Introduction to NVivo
This half-day workshop provides an introduction to using NVivo as a research tool. The workshop will explore how NVivo can be used to assist with various research activities including how to import and create sources in NVivo; creating links, memos and annotations within a project; visualising data via charts and graphs, and creating reports. All of the topics covered will involve practical, hands on activities for participants to explore a data set themselves and begin to familiarise themselves with NVivo.

Introduction to Statistical Methods
An introduction to the role that statistical inference and hypothesis testing play in quantitative analysis in research, and an overview of some simple but commonly used statistical tests.

Introduction to SPSS
The aim of this workshop is to provide a hands-on introduction to the statistical software SPSS. The primary focus of the workshop is on the entry, formatting, editing, manipulation and coding of data for later analysis. The workshop will also cover importing data from non-SPSS formats into SPSS and will briefly cover the help facilities available within SPSS and other useful learning resources and videos aimed at learning how to use it. The workshop also looks at the uses of SPSS how to obtain simple data summaries and graphs/charts.

Basic R
R is a quantitative software package that has the advantages of being free and having a lively and helpful user community.  It does, however, have the disadvantage of being code based.  For this workshop the assumption is that individuals have no knowledge of using any kind of command line interface.  Although front ends are available for R, they will not be used.  The following areas will be covered in this half day workshop:

  • What is R?
  • Data and first steps
  • Running simple analyses
  • Simple charts
  • Basic programming in R


The below workshops assume participants have some basic knowledge of statistic inference, such as through attendance at the previous workshop ‘Introduction to Statistical Methodology’. The workshops also assume participants have a basic knowledge of data entry and manipulation with SPSS, such as through attendance at the previous workshop entitled ‘Introduction to SPSS’.

A lot of data collected in research is in the form of categorical (or Nominal) data. Often there is an interest in understanding whether the data from the sample provide sufficient evidence to support the hypothesis that two such categorical variables are related (associated). The aim of this workshop is provide a hands-on introduction to a statistical test called the chi-squared test that can be used to test such a hypothesis.

The aim of this workshop is to provide a hands-on introduction to two statistical methods: paired and unpaired tests. These can be used to compare the mean responses between two groups or two sets (pairs) of responses from the same individuals.

One Factor ANOVA
The aim of this workshop is to provide a hands-on introduction to Analysis of Variance (ANOVA) when there is just one factor (grouping variable). This is an extension of the use of t-tests which can be used to compare two groups, whereas one factor ANOVA can be used to compare three or more groups.

Non-parametric Tests
The aim of this workshop is to provide a hands-on introduction to non-parametric statistical tests. This includes the Mann-Whitney test, the Wilcoxon Signed Rank test and the Kruskal-Wallis test.

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