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Unit information: Advanced Quantitative Research in 2020/21

Unit name Advanced Quantitative Research
Unit code SOCIM3133
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Dr. Phil Sayer
Open unit status Not open
Pre-requisites

Introduction to Quantitative Research Methods or equivalent.

Co-requisites

None

School/department School of Sociology, Politics and International Studies
Faculty Faculty of Social Sciences and Law

Description

Building on the teaching provided in the unit, Quantitative Social Research, this covers more advanced techniques of quantitative analysis; problems that commonly occur and the various methods of presentation of quantitative material. Specific topics include normal distributions and t-tests; ANOVA; correlation and regression; multivariate linear regression; residuals and interaction; logistic regression; log linear models; factor analysis; the use of comparative datasets; and the writing of quantitative reports.

Aims:

  • To familiarise students with aspects of computing most relevant to analysis of quantitative datasets in sociological research
  • To make students aware of the range of quantitative social research methods and their appropriateness for specific tasks and research questions
  • To provide practical training in data handling and in medium-level and more advanced statistical techniques of multivariate analysis using SPSS for Windows
  • To encourage an enquiring and critical approach to data analysis
  • To give students a realistic experience of quantitative research based on the analysis of a full secondary dataset

Intended learning outcomes

  • An awareness of main secondary data sources and the ability to access them
  • Capacity to investigate a substantive area of sociological interest using appropriate quantitative tools
  • A wareness of shoengths and limitations of data sources and analytical teclmiques
  • Ability to utilise data analysis software with proficiency and confidence
  • Capacity to evaluate the research practice, data and interpretations of others
  • Ability to communicate results of data analYsis both in writiIl& and verbally

Teaching details

The unit will be taught through blended learning methods, including a mix of synchronous and asynchronous teaching activities

Assessment Details

Students will be assessed by one coursework project at the end of the Semester. This will take the form of a detailed piece of analysis of a survey dataset, equivalent to a 4000 word essay.

Reading and References

  • Byrne, D (2002) interpreting Quantitative Data, Sage
  • De Vaus, D.A (1996) Surveys in Social Research, UeL Press
  • Fielding, J and Gilbert, N (2000) Understanding Social Statistics, Sage
  • Grimm, L., & Paul Yarnold Paperback (1998). Reading and Understanding Multivariate Statistics.
  • American Psychological Association
  • Miller, R., Acton, c., Fullerton, D and Maltby, J. (2002) SPSSfor Social Scientists Palgrave.

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