Overview

This unit provides students with knowledge regarding multivariate data procedures in conduct of academic research. This unit is designed to fill the gaps in data analysis using sophisticated approaches and data collection methods. The aim is to provide knowledge of available data analysis techniques to address specific research questions, their strengths and weaknesses (limitations) and the relevance to research design and sampling issues.

Requisites

Teaching Periods
Location
Start and end dates
Last self-enrolment date
Census date
Last withdraw without fail date
Results released date
Semester 1
Location
Hawthorn
Start and end dates
26-February-2024
26-May-2024
Last self-enrolment date
10-March-2024
Census date
31-March-2024
Last withdraw without fail date
12-April-2024
Results released date
02-July-2024

Learning outcomes

Students who successfully complete this unit will be able to:

  • Apply coherent and advanced knowledge of a range of data analysis procedures that may be appropriate when examining business issues
  • Apply quantitative research fundamentals to the analysis, design and application of research methods and to identify, specify and run the various software programs
  • Apply knowledge of research principles and methods to interpret the output of various data analysis procedures using the appropriate tools
  • Apply coherent and advanced knowledge of the design of quantitative research and implications for sampling and sampling units
  • Apply knowledge of research principles and methods to plan and execute a piece of research to demonstrate validity, reliability and generalisability
  • Communicate proficiently in professional practice to a variety of audiences and function as an effective member or leader of a team

Teaching methods

Hawthorn

Type Hours per week Number of weeks Total (number of hours)
On-campus
Class		2.00 12 weeks 24
Online
Lecture		1.00 12 weeks 12
Unspecified Activities
Independent Learning		9.50 12 weeks 114
TOTAL150

Assessment

Type Task Weighting ULO's
Assignment 1Group 20 - 30% 1,4,5,6 
Assignment 2Individual 30 - 40% 1,2,3,5 
Assignment 3Individual 30 - 50% 1,3 

Content

  • Basics of numbers, measurement and error
  • Reliability and Validity
  • Generalisability
  • Scales
  • Missing data
  • Univariate methods
  • Multivariate methods
  • Structural equation modelling
  • Experimental design

Study resources

Reading materials

A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.