Introduction to Quantitative Analysis
Postgraduate: Level 7
Thursday 08 October 2020
Friday 18 December 2020
29 June 2020
Requisites for this module
MSC B99012 Health Research,
MA M90012 Criminology,
MSC MF9012 Organised Crime, Terrorism and Security,
MA L30112 Sociological Research Methods,
MSC L31012 Survey Methods for Social Research,
MSC L310MO Survey Methods for Social Research,
MSC L31112 Migration Studies,
MSC L31124 Migration Studies,
PHD ML9048 Criminology,
MPHDB79748 Health Studies,
PHD B79748 Health Studies,
MSOCMX98 Criminology (Including Placement Year),
MSOCMX99 Criminology (Including Year Abroad)
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 note that assessment information is currently showing for 2019-20 and will be updated in September.
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.
No information available.
- Agresti, Alan; Finlay, Barbara; dawsonera. (2014) Statistical methods for the social sciences, Upper Saddle River, New Jersey: Pearson Prentice Hall.
- Netemeyer, Richard G.; Bearden, William O.; Sharma, Subhash. (c2003) Scaling procedures: issues and applications, Thousand Oaks, Calif: Sage Publications.
- Treiman, Donald J. (c2009) Quantitative data analysis: doing social research to test ideas, San Francisco, CA: Jossey-Bass.
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
||Moodle Quiz week 5
Additional coursework information
The course is assessed with two written assignments. The first is a short exercise that contributes 30% towards overall module mark; the second is a more substantial data analysis exercise (70% towards overall module mark).
Please note that assessment information is currently showing for 2018-19 and will be updated in August 2019
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Module supervisor and teaching staff
Prof Nick Allum, email: firstname.lastname@example.org.
Prof Ayse Guveli, email: email@example.com.
Prof Renee Luthra, 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
Prof Benjamin Bradford
University College London
Available via Moodle
Of 1160 hours, 0 (0%) hours available to students:
1158 hours not recorded due to service coverage or fault;
2 hours not recorded due to opt-out by lecturer(s).
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