Module code: SOC2031

Module Overview

This module builds upon the year 1 quantitative methods module introducing multivariate quantitative analyses with the help of the software package, SPSS. The module consists of a mix of lectures followed by guided classes where students will investigate the chosen topic, using a data set sourced from the UK Data Service and using SPSS. Students shall also learn how to interpret and present results of quantitative analyses.

Module provider


Module Leader

SETTY Emily (Sociology)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 128

Lecture Hours: 5

Practical/Performance Hours: 17

Module Availability

Semester 2

Prerequisites / Co-requisites

Quantitative Methods 1

Module content

Indicative content includes:

·         Creating new data files from survey questionnaires using SPSS

·         Sourcing quantitative data for secondary analysis

·         Data management procedures using SPSS

·         The logic behind simple and multiple regression analysis

·         The practical application of simple and multiple regression using SPSS

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework EXERCISE 1 30
Coursework EXERCISE 2 70

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate their understanding of the basic principles of statistics for social research including both statistical concepts and the use of software to demonstrate those concepts practically. Continuous formative assessment in class will allow students to demonstrate

their appreciation of the potential of the statistical evaluation, manipulation and

interpretation of data, and also allow them to develop skills in the entering and analysing of

data with the SPSS package.


Thus, the summative assessment for this module consists of:

·         Two assessed exercises, including one short, 30% weighted, written exercise and one longer, 70% weighted, practical exercise to be completed with the aid of computer software.

·         Deadlines CW1: week 7; CW2: week 12


Formative assessment and feedback

Students receive feedback during practical classes and on feedback sheets provided

Individually on return of both assessed exercises. 

Module aims

  • To give students a thorough grasp of how to use SPSS, the most popular and one of the most powerful computer packages for analysing quantitative data
  • To explain regression and interval level data analysis in non-technical terms using SPSS
  • To be able to read, understand and present quantitative analyses

Learning outcomes

Attributes Developed
1 Be able to create simple data sets for statistical analysis using the personal computer PT
2 Be able to carry out simple statistical analyses on their own data set or on other secondary data sources CT
3 Be able to carry out simple data management tasks prior to statistical analysis PT
4 Be able to understand the logic behind, and the appropriate time to use regression analysis as a tool for social research KC
5 Be able to carry out a simple and multiple regression analysis using SPSS     PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Build on the basic principles and steps involved in the statistical analysis of quantitative data learnt in year 1. This module aims to encourage students to develop a practical understanding of when and how to use particular multi-variate statistical techniques to best research social processes using quantitative data. This will be achieved through lectures and practical exercises on a computer using the latest version of statistical software, SPSS.

The learning and teaching methods include:

·         5  x 1 hr Lectures

·         5 x 1 hr classes practical computer classes

·         6 x 2 hr classes practical computer classes


Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

Upon accessing the reading list, please search for the module using the module code: SOC2031

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Criminology BSc (Hons) 2 Compulsory A weighted aggregate mark of 40% is required to pass the module
Sociology BSc (Hons) 2 Compulsory A weighted aggregate mark of 40% is required to pass the module
Criminology and Sociology BSc (Hons) 2 Compulsory A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.