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2015/16 Taught Postgraduate Module Catalogue

LUBS5283M Advanced Quantitative Methods

15 creditsClass Size: 50

Module manager: Dr Nathaniel Boso
Email: n.boso@leeds.ac.uk

Taught: Semester 2 View Timetable

Year running 2015/16

Pre-requisite qualifications

All students participating in this module must already have obtained the required qualifications to enter the LUBS PhD programme. LUBS 5285M or equivelent knowledge of quantitative methods.

Pre-requisites

LUBS5285MIntroduction to Research Design and Data Analysis

This module is not approved as an Elective

Module summary

This module is a part of the LUBS PhD training programme. It builds on the basic exposure to quantitative methods provided in the introduction to research design and data analysis. The primary aim of the course will be to introduce you to contemporary advanced quantitative analysis techniques and to provide guidelines on how you can use these skills in your doctoral works and journal publications. The module is optional since you can choose to attend Advanced Quantitative Methods or Advanced Qualitative Methods. It is scheduled in semester two over three full days. The module assessment will be based on an analysis of a dataset provided on the VLE. The analysis must be written up as a manuscript, typically in a format for submission to a major journal. Specific guidelines will be provided on VLE prior to the start of the course. The report makes up 100% of the marks for this module.

Objectives

This module aims to build on the introductory training in quantitative methods provided in Introduction to Research Design and Data Analysis (LUBS 5285M), and to provide coverage of more advanced and contemporary quantitative approaches, focusing on developing students’ multivariate statistical analysis techniques: linear/mediation/moderation regression analyses; and structural equation modelling.

Learning outcomes
Upon completion of this module students will be able to critically assess:
- the underlying theory and application of the methods studied
- use of appropriate software packages to analyse quantitative datasets

Skills outcomes
Upon completion of this module students will be able to:
Subject Specific
- Conduct complex statistical analyses for their PhD dissertations and academic papers
- Present results of statistical analyses in conferences and in journal papers

Transferable
- Work effectively as an analyst
- Analyse and present reasoned and logical conclusions from a set of data
- Prepare and deliver an academic presentations


Syllabus

Indicative content
- Advanced Correlation & Regression Analysis
- Introduction to Structural Equation Modelling
- Exploratory and Confirmatory Factor Analysis
- Structural equation analysis
- Experimental Research Methods
- Laboratory experiments

Teaching methods

Delivery typeNumberLength hoursStudent hours
Workshop112.0022.00
Private study hours128.00
Total Contact hours22.00
Total hours (100hr per 10 credits)150.00

Private study

- Pre-workshop reading and preparation: 40 hours
- Post-workshop reading and practical work: 48 hours
- Revision for exam: 40 hours.

Opportunities for Formative Feedback

Given the level of the module much monitoring will be student-led, as reflection on one's progress and one's need for additional input are a requirement in an academic career and in most professional environments. Students will be encouraged in such reflection.

Outside of the workshop, students will be given the opportunity for feedback via telephone and/or email discussions with the tutor.

A discussion forum will also be set up on the VLE, through which students will be given additional opportunities for feedback and to raise questions with their tutors.

Methods of assessment


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 100.00
Total percentage (Assessment Exams)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 03/03/2015

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