Advanced Design and Data Analysis
Subject 512-422 (2008)
Note: This is an archived Handbook entry from 2008.Search for this in the current handbook
| Credit Points: | 12.500 | ||||||||||||
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| Level: | Undergraduate | ||||||||||||
| Dates & Locations: | This subject has the following teaching availabilities in 2008: Semester 1, - Taught on campus.
Timetable can be viewed here. For information about these dates, click here. | ||||||||||||
| Time Commitment: | Contact Hours: Twenty-four hours of lectures, 12 hours of laboratory classes. [Estimated total time commitment of 120 hours.] Total Time Commitment: Not available | ||||||||||||
| Prerequisites: | None | ||||||||||||
| Corequisites: | None | ||||||||||||
| Recommended Background Knowledge: | None | ||||||||||||
| Non Allowed Subjects: | None | ||||||||||||
| Core Participation Requirements: |
For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry. It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support: http://services.unimelb.edu.au/disability |
Coordinator
Assoc Prof Richard Bell| Subject Overview: | This subject provides an introduction to multivariate data analysis in the behavioural and social sciences, including the nature, rationale and application of a number of widely used multivariate data analysis models. For each model, issues covered include the nature of the model and its assumptions; situations in which the model might be applied; diagnostics for model adequacy; estimation and inference; interpretation; the use of the software package SPSS for model-fitting. Models will be selected from multiple regression; logistic regression; an introduction to path analysis; multivariate analysis of variance and discriminant analysis; principal components analysis and factor analysis; models for multivariate categorical data; cluster analysis and multidimensional scaling. |
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| Assessment: | A written report of no more than 1500 words (40%), and an examination of no more than two hours (60%).Each piece of assessment must be completed (hurdle requirement).Attendance at 80% or more of the laboratory classes is a hurdle requirement. In case of failure to meet the hurdle requirement, additional work will be required before a passing grade can be awarded. |
| Prescribed Texts: | None |
| Recommended Texts: | Information Not Available |
| Breadth Options: | This subject is not available as a breadth subject. |
| Fees Information: | Subject EFTSL, Level, Discipline & Census Date |
| Generic Skills: | On completion of this subject, students should have a greater ability to: design research studies requiring complex quantitative observations; present and analyse complex quantitative information; and critically evaluate and interpret complex quantitative information. |
| Related Course(s): |
Bachelor of Arts (Honours) in Psychology Bachelor of Science (Honours) in Psychology |
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