units

DPSY5103

Faculty of Medicine, Nursing and Health Sciences

18 September 2017 22 November 2024
Monash University

Postgraduate - Unit

This unit entry is for students who completed this unit in 2012 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

0 points, SCA Band 1, 0.000 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

LevelPostgraduate
FacultyFaculty of Medicine, Nursing and Health Sciences
OfferedClayton First semester 2012 (Day)
Coordinator(s)TBA

Synopsis

This unit will equip students with the necessary skills to undertake research. Nonetheless, the primary motivation for this course concerns future employment. Research design and analysis are critical components of both academic and professional psychology.

Outcomes

This unit equips students with the necessary skills they need to design research and analyse data for their thesis, placements, and employment. After completing this unit successfully, students should be able to undertake a comprehensive program evaluation as well as a single subject design, and complete their thesis, confidently, competently, and independently.

Specifically, students should be able to:

  • Understand and design the main phases of the key research approaches, including program evaluations, single subject designs, experiments, quasi-experiments, and qualitative projects;
  • Accommodate the considerations and complications of these approaches, such as sampling biases, spurious variables, common method variance, suppressors, non-recursive relationships, confounds, consequential validity, asymmetric transfer, mediators, moderators, stakeholder needs, economic evaluation, family wise errors, power, autocorrelation, and nonlinear dynamics;
  • Apply multivariate statistics techniques to address some of these complications, such as ANCOVA, discriminant function analysis, logistic regression analysis, multiple regression analysis, canonical correlation, and factor analysis;
  • Recognize the fundamental principles of more advanced concepts, which can then be explored through additional reading, including HLM, grounded theory, survival analyses, meta-analyses, catastrophe theory, signal detection theory, ARIMA, interim designs, Bayesian theory, and structural equation modelling;
  • Develop creative and insightful methods to maximise the utility of research; and
  • Justify and report the procedures and techniques that were utilised.

Assessment

The assessment will comprise two components: a journal (60%) and a multiple-choice examination (40%).

Chief examiner(s)

Prof Graeme Coleman