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Undergraduate Module Descriptors 2012/13

CRI210: Quantitative Methods Social Sciences

Module Title Quantitative Methods Social Sciences
Module Code CRI210
Module Tutor Charlotte Parker
School Natural and Social Sciences
CAT Points 15
Level of Study 5
Pre-requisites Before taking this module you must pass 1 module from {SY104, SY111, CRI111, GEO111}
Co-requisites None
Restrictions None
Brief Description

This module is mainly concerned with mastering SPSS for Windows, the most popular and one of the most powerful computer packages for analysing quantitative data. Each session will consist of a short lecture followed by practical work to give students a thorough grasp of how to use this package on a personal computer.

Indicative Syllabus

This module focuses on key skills and concepts in quantitative data analysis. Content will include:

a)   discussion of when and how to use statistical techniques rather than theoretical derivations;
b)   secondary analysis of data;
c)   familiarisation with SPSS for Windows computer package.

Learning Outcomes

i. Knowledge and understanding
This module is designed to give students a basic grasp of the statistical techniques necessary for understanding and/or implementation of social research. No knowledge of post GCSE mathematics is assumed. In particular, having completed this module, students should be able to:
a)  create simple data sets for statistical analysis using a personal computer;
b)  carry out simple statistical analyses on their own data set or other secondary data sources;
c)  undertake simple data management tasks prior to statistical analysis;
d) analyse secondary data using simple statistical techniques using the software package SPSS.



ii Skills
At the end of this module, students should have the skill to understand and use the following data and research concepts:
a)  measures of central tendency and dispersion; elementary probability; common distributions; sampling distributions; elementary statistical inference; estimation and hypothesis testing; contingency tables, bi-variate correlation and regression;
b)  students should also be able to understand and describe the content of statistical tables derived from published statistical sources)  they should also be able to search for appropriate data for secondary quantitative analysis using the WWW.

Learning and Teaching Activities Staff / student contact: 30% (36 hrs; lectures, practicals)
Student private study: 70%
Assessment (For further details see the Module Guide) 001: 50% Coursework: Project report: 2000 words or equivalent
002: 50% Coursework: Project report: 2000 words or equivalent
Special Assessment Requirements None
Indicative Resources

The Library Catalogue contains full details of the current reading list for this module. Further details may also be found in the Module Guide.

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