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Unit information: Advanced Quantitative Methods in the Social Sciences in 2021/22

Unit name Advanced Quantitative Methods in the Social Sciences
Unit code EDUCM0054
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Leckie
Open unit status Not open

Familiarity with basic descriptive and inferential statistics and the SPSS software to the level covered in EDUCM5504 Statistics in Education / EDUCM0003 Introduction to Quantitative Methods in the Social Sciences. Students should therefore be confident producing and interpreting standard summary statistics, data tabulations, graphs, 95% confidence intervals around sample means, t-tests and correlation coefficients.



School/department School of Education
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

The unit will introduce students to a range of multivariate statistical methods widely applied in quantitative educational research. The philosophy of this course is that students will learn more by applying these methods using the SPSS software and to real education and social science datasets than by focusing solely on their underlying statistical theory. Methods covered include: analysis of variance, factor analysis, linear regression, and multilevel modelling.

The unit aims to:

  • introduce the main multivariate statistical methods used in educational and social research (ANOVA, factor analysis, linear regression, multilevel modelling)
  • provide students with an understanding of when these methods are appropriate and how these methods can contribute to a more robust/powerful evidence base in educational research;
  • provide students with the knowledge and skills to apply these methods to secondary datasets using the SPSS computer package and to interpret their statistical output in relation to specific research questions.
  • develop students’ ability to statistically critique published research.

Intended Learning Outcomes

Upon successful completion of this unit students will be able to demonstrate that they:

  1. Understand which multivariate statistical methods (ANOVA, factor analysis, linear regression, multilevel modelling) are appropriate in different data situations and for addressing different research questions.
  2. Have a working knowledge of these methods and to be able to apply them to data in SPSS and be able to interpret the resulting statistics appropriately.
  3. Are able to select relevant information from SPSS statistical output and present the results in a format appropriate for publication.
  4. Can statistically critique published research which uses these methods.

Teaching Information

This unit will be taught using a blended approach consisting of a mixture of synchronous and asynchronous activities including lectures, computer practicals using SPSS software, and critical reading and discussion of published quantitative articles.

Assessment Information

Formative assessment:

Regular SPSS worksheets will be provided in which students attempt to apply the taught methods to data and to interpret the results. Annotated answers will then be provided, allowing students to check their progress.

Students will also have the opportunity to post questions and receive feedback on the unit material, SPSS and general questions about the assignment.

Summative assessment:

The summative assessment consists of a structured assignment with several sections. In each section, students will be required to identify the appropriate method for the given research question and SPSS dataset. They will then have to apply the method and associated descriptive statistics in SPSS, present the results in the format of an academic report, and give a critical interpretation of the findings, reflect on the strengths and weaknesses of their analyses, and suggest potential improvements. (4,000 words equivalent). ILOs 1-3


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. EDUCM0054).

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.

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.