2019/20 Taught Postgraduate Module Catalogue
LUBS5283M Advanced Quantitative Methods
15 creditsClass Size: 50
Module manager: Li Zheng
Taught: Semester 2 View Timetable
Year running 2019/20
Pre-requisite qualificationsAll 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.
|LUBS5285M||Introduction to Research Design and Data Analysis|
This module is not approved as an Elective
Module summaryThis 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 a draft paper which must include all analysis, table, figures and description of the results. Students will choose their own topics that apply or develop appropriate statistical models to an important substantive problem. The draft paper makes up 100% of the marks for this module.
ObjectivesThis 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.
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
Upon completion of this module students will be able to:
- Conduct complex statistical analyses for their PhD dissertations and academic papers
- Present results of statistical analyses in conferences and in journal papers
- Work effectively as an analyst
- Analyse and present reasoned and logical conclusions from a set of data
- Prepare and deliver an academic presentations
- Factor analysis: exploratory factor analysis vs. confirm factor analysis
- Measurement: reflective vs. formative
- Introduction to structural equation modelling
- Dealing with endogeneity issue
- Dealing with multi-method research
- Experiment design
- Discussion moderator and mediator effect
|Delivery type||Number||Length hours||Student hours|
|Private study hours||126.00|
|Total Contact hours||24.00|
|Total hours (100hr per 10 credits)||150.00|
Private study- Pre-workshop reading and preparation: 40 hours
- Post-workshop reading and practical work: 46 hours
- Revision for exam: 40 hours.
Opportunities for Formative FeedbackGiven 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
|Assessment type||Notes||% of formal assessment|
|Total percentage (Assessment Coursework)||100.00|
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
Reading listThe reading list is available from the Library website
Last updated: 22/01/2020 11:16:56
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