Introduction to Quantitative Analysis
Postgraduate: Level 7
Thursday 03 October 2019
Saturday 14 December 2019
23 August 2019
Requisites for this module
MSC B99012 Health Research,
MSC B990MO Health Research,
MA M90012 Criminology,
MA L30112 Sociological Research Methods,
MSC L31012 Survey Methods for Social Research,
MSC L310MO Survey Methods for Social Research,
MSC L31112 Migration Studies
This module is a practical introduction to analysing quantitative data. Using a combination of lecture and computer lab based formats, the module is intended to provide participants with an understanding of the principles of quantitative data analysis and their practical application. The primary focus is on the application of statistical techniques for analysing survey data, although the methods covered are applicable to many other forms of quantitative data. As well as enabling participants to conduct investigations relevant to their own research, it will also equip them to be a critical user of other research.
The aim of the course is to introduce students who have little experience of quantitative methods to basic and intermediate statistical concepts and procedures. The emphasis is on practical applications, not mathematics (but a small amount of very elementary maths is, inevitably, required!). The teaching is carried out with a combination of lectures, classes and computer lab sessions.
By the end of course you should be able to:
• understand the logic of statistical description and inference
• critically evaluate research articles that use statistics
• understand the link between substantive theory and statistical models
• carry out elementary and intermediate statistical analysis using STATA 14
Please be aware that this module includes a lot of incremental work and you will need to attend each week. You will also need to use computer software only available in the campus IT labs in order to complete assessments. The module does not lend itself to home study.
- Mehmetoglu, Mehmet; Jakobsen, Tor G. (©2017) Applied statistics using Stata: a guide for the social sciences, London: Sage Publications.
The above list is indicative of the essential reading for the course. The library makes provision for all reading list items, with digital provision where possible, and these resources are shared between students. Further reading can be obtained from this module's reading list.
Assessment items, weightings and deadlines
|Coursework / exam
Module supervisor and teaching staff
Prof Nick Allum, email: firstname.lastname@example.org.
Dr Nick Allum
Michele Hall, Graduate Administrator, Telephone 01206 873051, Email: email@example.com
Prof Paul Stretesky
The University of Northumbria at Newcastle
Professor of Criminology
Available via Moodle
Of 30 hours, 10 (33.3%) hours available to students:
20 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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