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2010/1 Module Catalogue
 Module Code: SOC2001 Module Title: QUANTITATIVE METHODS 2
Module Provider: Sociology Short Name: SOC207
Level: HE2 Module Co-ordinator: FIELDING JL Dr (Sociology)
Number of credits: 20 Number of ECTS credits: 10
 
Module Availability

Year

Assessment Pattern

Unit(s) of Assessment
Weighting Towards Module Mark (%)
One practical computing exercise
50%
One practical statistical exercise
50%

Module Overview

The first 10 sessions consist of a short lecture followed by a practical 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, on a personal computer.

 

 

The following sessions take a very hands-on approach.  Under supervision and in a step-by-step manner, you will investigate the chosen topic, with a data set sourced from the Data Archive at the University of Essex and using SPSS.  We shall also learn how to interpret and present results of quantitative analyses.

 

 

The first part of the course is mainly concerned with giving students a thorough grasp of SPSS. The second part aims to explain regression and interval level data in non-technical terms using SPSS.

 

Prerequisites/Co-requisites
Module SOC1007 - Quantitative Methods 1.
Module Aims

During the Autumn semester each session consists of a short lecture followed by a practical 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, on a personal computer.

 

 

 

 

In the Spring semester the course takes a very hands-on approach.  Under supervision and in a step-by-step manner, you will investigate the chosen topic, with a data set sourced from the Data Archive at the University of Essex and using SPSS.  We shall also learn how to interpret and present results of quantitative analyses.

 

 

 

 

The Autumn semester course is mainly concerned with giving students a thorough grasp of SPSS.    The Spring semester course aims to explain regression and interval level data in non-technical terms using SPSS.

 

 

Learning Outcomes

Having completed this module students should:

 

·         Be able to create simple data sets for statistical analysis using the personal computer.

 

·         Be able to carry out simple statistical analyses on their own data set or on other secondary data sources.

 

·         Be able to carry out simple data management tasks prior to statistical analysis.

 

·         Be able to understand the logic behind, and the appropriate time to use regression analysis as a tool for social research.

 

·         Be able to carry out a regression analysis using SPSS.

 

·         Be able to understand and describe the content of statistical tables derived from published statistical sources.

 

·         Be able to search for appropriate data for secondary quantitative analysis using online data archives.

 

Module Content
Methods of Teaching/Learning

Lectures and classes

Selected Texts/Journals

Agresti A and B Finlay (1997) Statistical Methods for the Social Sciences 3rd edn, Prentice-Hall

 

Allison PD (1999) Multiple Regression: A Primer, Pine Forge Press

 

Fielding J and N. Gilbert (2000) Understanding Social Statistics, Sage

 

Freedman D, R Pisani, R Purves and A Adikhari (1997) 3rd edn, Norton

 

Norusis M (1998) SPSS Base 8.0 Users Guide, SPSS Inc

 

Norusis M (1999) The SPSS 9.0 Guide to Data Analysis, Prentice Hall

 

Wallgren A (1997) Graphing Statistics, Sage

 

 

Last Updated

September 2010