| Unit name | Advanced Quantitative Research Methods |
|---|---|
| Unit code | SSLFM0003 |
| 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 |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | Social Sciences and Law Faculty Office |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
This unit develops researcher understanding of advanced quantitative research methods that are widely applied in the social sciences. The unit will relate different research questions and study designs to the appropriate quantitative methods to use to answer them. The unit will give background about each method, the assumptions it makes and how the results of using the method in commonly used statistical software can be interpreted. The topics to be covered include both statistical approaches for performing data analysis and hypothesis testing in commonly occurring study designs as well as methods that can be used for data reduction.
This unit is hosted by the Faculty of Arts, Law and Social Sciences, meaning that students will engage with interdisciplinary conversations involving peers from across the faculty. As a result, students’ epistemological, ontological, and methodological perspectives may be broadened or challenged through engaging in diverse conversations. This unit is integral for anyone engaged in Quantitative Research at a postgraduate research level.
How does this unit fit into your programme of study?
This unit is part of the core South West Doctoral Training Partnership training and Faculty-level training in research methods for postgraduate research students. This research methods training is designed to develop students’ research skills, so that they can design and conduct high-quality research in their area of interest. The core understanding developed in this unit builds on Introduction to Research Methods in the Social Sciences, and gives researchers who choose it broader knowledge of quantitative methods. As a result, this unit will facilitate a deeper engagement with questions, complexities, and methodological issues arising from engaging with research areas via quantitative research methods.
An overview of content
This unit will cover a range of advanced quantitative research methods used in social science research. These include statistical models used for answering more advanced research questions and where more complex study designs are applied, for example regression (both linear and logistic), ANOVA and multilevel modelling. They also include approaches for data reduction such as factor analysis. All methods will be motivated by problems and datasets from across the social sciences and students will be taught how to use statistical software to answer the research questions.
How will students, personally, be different as a result of the unit
Through taking this unit, students will develop methodological and skills-related knowledge, as well as a deeper understanding of how to measure and approach methodological quality in quantitative research. Students will be able to effectively conduct quantitative research, with attention given on how to choose the appropriate statistical methodological approach and software to answer specific research questions for the data collected.
Learning outcomes
Upon successful completion of the unit, students will be able to:
Teaching on this unit takes place throughout teaching block 2, weeks 13-24. Teaching and learning will be performed using a flipped classroom approach, to allow the students to revisit topics they find difficult and maximise the interaction with staff on practical aspects of analysis during class time. Each week will involve:
Tasks which help you learn and prepare you for summative tasks (formative)
Weekly practicals involving statistical software exercises and paper discussions will allow students to develop the practical skills required and annotated answers will then be provided to allow students to monitor their progress.
Tasks which count towards your unit mark (summative):
The assessment for this unit will be in the form of a 4000 word report of the statistical analysis of several supplied datasets and research questions. For each question, the student is required to decide on the appropriate technique to use, implement their statistical analysis in appropriate software and write a short report of the findings, appropriately interpreting the software output and critiquing the study design. 100% (Assesses ILOs 1-3)
When assessment does not go to plan
So long as the overall average grade for summative assessments is 50 or higher, students will pass this class. When a student fails the unit and is eligible to resubmit, failed components will be reassessed on a like-for-like basis. The students will be asked to resubmit a revised version of their previous assignment.
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. SSLFM0003).
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 University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
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. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
