University of Sydney Handbooks - 2018 Archive

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Units of study for Postgraduate Research

The information below relates to the units of study for the current year.

Table of Postgraduate Research units of study

Unit of study Credit points A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition Session
BUSS7901
Research Design
6   

For MPhil and PhD students only.
Semester 1
Semester 2
BUSS7902
Quantitative and Qualitative Research Methods
6    N BUSS7903


For MPhil and PhD students only.
Semester 1
Semester 2
BUSS7904
Advanced Quantitative Methods
6    A BUSS7902
N ECOF7904


For MPhil and PhD students only.
Semester 1
Semester 2
BUSS7906
Advanced Qualitative Methods
6    A BUSS7902
N ECOF7906


For MPhil and PhD students only.
Semester 1
Semester 2
BUSS7907
Applied Quantitative Analysis
6    A BUSS7902 and BUSS7904
N ECOF7907


For MPhil and PhD students only.
Semester 1
Semester 2
BUSS7908
Research Readings Seminar
6   

For MPhil and PhD students only
Semester 1
Semester 2

Postgraduate Research units of study descriptions

BUSS7901 Research Design

Credit points: 6 Session: Semester 1,Semester 2 Classes: 24 lectures for this unit Assessment: critical literature review (25%), concise research proposal (45%), presentation of research proposal (15%), peer marketing assignment (10%), in-class participation (5%) Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only.
The unit provides PGR candidates with an understanding of the research design as the foundation for effective and interesting research. It emphasises a systematic approach to developing rigour in research design, building theoretical and paradigmatic links from a research idea to the design of research methods.
BUSS7902 Quantitative and Qualitative Research Methods

Credit points: 6 Session: Semester 1,Semester 2 Classes: 3 hrs per week Prohibitions: BUSS7903 Assessment: research ideas (qualitative) (15%), research report I (quantitative) (30%), self-assessment of research report I (5%), research ideas (qualitative) (10%), discussion leadership session (15%), research report II (qualitative) (25%) Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only.
This unit is intended to introduce PhD students in the University of Sydney Business School to two streams of techniques for research. The first stream (Quantitative Analysis) provides students with a review or introduction to the types of quantitative analysis techniques that they may be required to know, discuss or conduct, both during their PhD and in their future working lives. This stream aims to provide a basic training with a focus on statistical and business analysis methods. The skills taught in this stream are considered important for all PhD candidates to possess, both during and after their candidature. Students learn the different methods that can be applied to both continuous and discrete data. The second stream (Qualitative Analysis) introduces students to a broad range of philosophical approaches to research. Students also discover the practical implications for the research design accompanying each of the approaches. This stream introduces a broad range of interpretive approaches to research. Students learn to choose a methodological approach that is appropriate for particular interpretive research enquiry, keeping in mind the epistemological 'fit' with the research question. This stream also helps students understand the practical implications of adopting a particular methodological approach.
BUSS7904 Advanced Quantitative Methods

Credit points: 6 Session: Semester 1,Semester 2 Classes: Workshop, once a week, 3 hours per class Prohibitions: ECOF7904 Assumed knowledge: BUSS7902 Assessment: data analytics problem 1 (25%), data analytics problem 2 (25%), data analytics problem 3 (25%), data analytics problem 4 (25%). Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only.
This unit provides students with an introduction to advanced quantitative analysis techniques that they may be required to know, discuss or conduct, both during their PhD and in their future working lives. The unit is divided into four segments. The first segment reviews basic quantitative methods covered in BUSS7902 before considering issues around estimation and forecasting. Focus then switches to approaches for dealing with repeated measures including panel estimation methods and time series analysis, before consideration of ANOVA techniques and analogous non-parametric methods. Consideration is then given to the most widely used multivariate methods including factor analysis, multiple discriminant analysis, cluster analysis and structural equation modelling. The final segment covers categorical and discrete choice data analysis covering both the theory and practice of designing choice experiments and conducting sophisticated logit modelling applications. The unit covers both the theory and application of the various techniques with hands-on lab-based sessions and assignments crucial to the quality of the learning experience.
BUSS7906 Advanced Qualitative Methods

Credit points: 6 Session: Semester 1,Semester 2 Classes: Workshop, once a week, 3 hours per class Prohibitions: ECOF7906 Assumed knowledge: BUSS7902 Assessment: seminar preparation (30%), presentation (20%), individual reflection (10%), article comparison (40%) Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only.
The purpose of this unit is to extend and deepen students' knowledge of qualitative research gained in BUSS7902. Students participate in the key contemporary debates on qualitative research in business/management disciplines, and in the social sciences more broadly. The unit covers all stages of conducting a qualitative study, from research design to reporting the results of an empirical study. Emphasis is placed on the relevance of the researcher¿s own paradigmatic and disciplinary positioning, the diversity and evolution of qualitative traditions, and emerging trends. The implications of different ontological and philosophical commitments for the choices made during the course of a qualitative project are a key integrating theme of this unit. Upon completion of this unit, students are able to critically evaluate qualitative research, make informed decisions in the context of their own projects and improve their own research practices.
BUSS7907 Applied Quantitative Analysis

Credit points: 6 Session: Semester 1,Semester 2 Classes: Intensive - 5 days, 9am-5.30pm Prohibitions: ECOF7907 Assumed knowledge: BUSS7902 and BUSS7904 Assessment: stata, data management and programming (50%), copulas: multivariate distribution modelling (50%) Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only.
The unit aims to develop advanced quantitative research proficiencies for managing and analysing large-scale datasets, and applying advanced statistical and econometric techniques using real data. This is a hands-on workshop and all material is straightforwardly applied using the software Stata.
BUSS7908 Research Readings Seminar

Credit points: 6 Session: Semester 1,Semester 2 Classes: 20 lectures for this unit Assessment: essay / conversation starter (50%), final essay (50%) Mode of delivery: Normal (lecture/lab/tutorial) day
Note: For MPhil and PhD students only
This unit provides research candidates with the opportunity to gain in-depth business-related knowledge in their academic domain and assists them to engage in critical interrogation of academic work. Through reading and in-class discussions, candidates are exposed to seminal papers and key trends that influence the thinking within their discipline. The unit is seminar-based and candidates are expected to actively contribute to class discussions around readings and research ideas. Candidates submit a short written synthesis of the readings assigned for each session. Additionally, based on the readings and discussions, candidates write and present a 5,000 word final essay. Enrolment is limited to research candidates and is by special permission from each discipline and the Director of Doctoral Studies.