The Cathie Marsh Institute for Social Research short course training programme offers training at introductory, intermediate and advanced level in research methods and quantitative data analysis aimed at academics and applied researchers
in the public and private sectors.
Courses take place in the Humanities Bridgeford Street Building, University of Manchester.
CMIST has five courses coming up in February which have available places:-
·
Introduction to Statistics – 8 February 2017
·
Practical Skills for Data Analysts – 13 February
2017
·
NVivo for Qualitative Data and Corpus
Analysis – 16 February 2017
·
Latent Factor Analysis – 17 February 2017
·
Structural Equation Modelling using Mplus – 22-24
February 2017
Introduction to Statistics
Date: 8 February 2017, 10am – 4.30pm
Instructor: David Lee
Level: Introductory
Booking:
http://www.cmist.manchester.ac.uk/study/short/booking/
Fee: £140 for those from educational, government and charitable institutions; £195 others.
Outline
The aims of the course are to familiarise participants with some of the most commonly utilised statistical procedures using IBM SPSS, and to provide an introduction to the theory and methods of inferential statistical analysis using example
datasets and exercises.
By the end of the day participants will be familiar with how to access and run a range of key statistical procedures and be able to understand and interpret output generated by IBM SPSS.
Course Objectives
On completing the course, participants will have covered the following:
·
Drawing inferences about populations from a sample.
·
The importance of standard errors and confidence intervals.
·
Hypothesis testing and p-values.
·
Procedures in IBM SPSS to perform chi-squared tests, t-tests, analysis of variance, correlations, linear regression and logistic regression.
Practical Skills for Data Analysts
Date: 13 February 2017, 10am — 4:30pm
Instructor: Silvia Galandini
Level: Introductory
Booking:
http://www.cmist.manchester.ac.uk/study/short/booking/
Fee: £140 for those from educational, government and charitable institutions; £195 others.
Outline
This course will show participants how to use statistical analysis software, in this instance SPSS. In the course, participants will be introduced to the SPSS environment as well as useful key concepts (such as cases, variables, values,
and levels of measurement) to perform basic descriptive data analysis. A key component of the course involves getting familiar with basic SPSS data analysis commands in hands-on sessions. By the end of the day, participants will be familiar with the software;
know how to open a data file, enter data, and do basic data manipulations; and be able to produce simple descriptive statistics, one- and two-way tables, as well as simple graphs.
This is a foundation course that does not require any previous experience of SPSS and that will provide participants with the appropriate background to progress to other CMIST courses, particularly Introduction to Data Analysis 1 and Introduction
to Data Analysis 2.
Course Objectives
On completing the course, participants will have covered the following.
·
How to open and explore datasets.
·
Key procedures for data manipulation including sub-setting and variable recoding.
·
Procedures for producing simple descriptive statistics for all or subsets of your cases.
·
Procedures for producing graphical output.
NVivo for Qualitative Data and Corpus Analysis
Date: 16 February 2017, 9:00am - 5pm
Instructor: Wendy Olsen
Level: Introductory
Booking:
http://www.cmist.manchester.ac.uk/study/short/booking/
Fee: £140 for those from educational, government and charitable institutions; £195 others.
Outline
This course introduces NVIVO and uses various menu option in NVIVO to analyse data.
The structure of the training session will be a combination of formal presentation alongside practical application. Those attending the training session will have access to data sets for practical sessions and can also bring their own data
to use in the practical parts of the session. Among the methods we teach in the morning are: coding, browsing, queries, models, and viewing the coding stripes.
In the afternoon, an advanced application is considered. We look at the data in terms of comparing one empirical corpus with a larger, linguistic corpus. The terms keyness, discourses, concordance, agent, dominant discourses, deviant
discourses, tropes and intertextuality (based in part on the work of Norman Fairclough) are used in developing an argument as follows. Those with medium-to-large databases may wish to interpret mainly a few key dominant discourses and the deviant variants
that are closely related and comparable to them. The corpus analysis method enables a keyness measure to be calculated, and the most prominent discourse topics discovered. An interpretation is offered as an example using real data from South and North India.
Methodologically this offers rigour, transparency, and sophistication as well as originality for a qualitative analysis.
Course Objectives
·
To explore all the basic, intermediate and advanced menu options in NVIVO software
·
To analyse qualitative data in a transparent, reproducible way so that teams can work on the database
·
To do mixed methods research using a partly systematic ‘keyness’ analysis of a corpus (body) of qualitative data.
·
To interpret discourses and intertextuality of deviant and dominant discourses in a data set.
Latent Factor Analysis
Date: 17 February 2017, 9:30am – 4.30pm
Instructor: Bram Vanhoutte
Level: Intermediate
Booking:
http://www.cmist.manchester.ac.uk/study/short/booking/
Fee: £140 for those from educational, government and charitable institutions; £195 others.
Outline
This short course covers latent variables and factor analysis at an introductory and intermediate level. A latent variable is something invisible (such as a concept, an attitude, or an illness) that cannot be measured directly, but that
has been measured using a set of related observed indicators.
Factor analysis is one way to derive a factor from a set of variables, and is thus called a data reduction method. Other data reduction methods include principal components analysis, which is very closely related to factor analysis, and
multiple correspondence analysis.
We will cover both exploratory and confirmatory factor analysis, and highlight their differences. More advanced topics, such as testing for measurement equivalence, will also be touched upon. The course is suitable both for primary-data
collection researchers (who may need to write a suitable questionnaire), and for those who want to analyse data sets, with a focus on measurement issues.
Course Objectives
·
Master the basics of factor analysis
·
Learn to test how many factors are needed in a factor model
·
Explore more advanced confirmatory models for coping with measurement artefacts and test for measurement equivalence
·
Help participants become familiar with examples from social science research where latent variables are useful
Structural Equation Modelling using Mplus
Date: 22-24 February 2017
Instructor: Nick Shryane
Level: Intermediate
Booking:
http://www.cmist.manchester.ac.uk/study/short/booking/
Fee: £420 for those from educational, government and charitable institutions; £585 others.
Outline
Structural Equation Models (SEM) amalgamate regression analysis, path/mediation analysis and factor analysis, allowing for more richly detailed statistical models to be specified and compared to data than by using these techniques individually.
Historically, SEM models were confined to the analysis of continuous observed data, limiting their usefulness in applied social research, where many phenomena are inherently discrete or are measured only with coarse-grained instruments.
Advances in recent years have made available SEM methods for categorical data to applied researchers. This course covers both linear SEM and generalized SEM for non-continuous outcomes, as well as models with non-continuous latent variables,
i.e. latent classes.
Course Objectives
This course aims to train quantitative social scientists to use the Mplus programme in the application of structural equation modelling techniques to continuous and non-continuous observed data.
The course also aims to integrate approaches that assume latent dimensions of variation (eg factor analysis) with approaches that assume unobserved groups or categories (eg latent class analysis).
Full details of all CMIST Courses and booking via
http://www.cmist.manchester.ac.uk/study/short/list/
CMIST | G9 Humanities Bridgeford Street | University of Manchester | Manchester | M13 9PL
Tel 0161 275 0796