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Unit information: Advanced Quantitative Research in 2021/22

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. Sims
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 including Unit Aims

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 Information

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

Assessment Information

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.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. SOCIM3133).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.

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