Course Title: Advanced Statistical Analysis

Part A: Course Overview

Course Title: Advanced Statistical Analysis

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1233

Bundoora Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 2 2006,
Sem 2 2007,
Sem 2 2008,
Sem 2 2009,
Sem 2 2010,
Sem 2 2011,
Sem 2 2013

MATH2214

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

Sem 2 2014,
Sem 2 2015,
Sem 2 2016

MATH2214

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020

Course Coordinator: Assoc. Prof. Cliff da Costa

Course Coordinator Phone: +61 3 9925 6114

Course Coordinator Email: cliff.dacosta@rmit.edu.au

Course Coordinator Location: 251.2.67, Bundoora East Campus


Pre-requisite Courses and Assumed Knowledge and Capabilities

 

Third year psychology students should have obtained at least a credit in all of the following: MATH1275/1276, MATH1277/1278, MATH1279/1280, MATH1281/1282

Non-psychology students must have obtained at least a credit on an equivalent 2nd year level statistics course.

Above requirements need to be fulfilled prior to enrolling in the course.

If in doubt, contact the course coordinator.

 

Students intending to enrol should be familiar with the use of the statistical package spss or its equivalent


Course Description

 

This course is geared towards applying advanced multivariate statistical methods to data in the fields of Psychology and the Health Sciences.

It is offered to students in their third year of study in Psychology and the Health Sciences who intend to do an Honours/Masters/PhD on completion of their Undergraduate Program.

Tentative Topics Covered: Repeated measures anova including mixed designs, manova, discriminant analysis, ancova, logistic regression, multilevel modelling, assessing reliability of items in a rating scale, factor analysis, meta-analysis


Objectives/Learning Outcomes/Capability Development

This course is a student option offered to students completing the undergraduate Psychology course (BP154) and other Health Sciences students enrolled in a 3rd Year Program at RMIT. As such it contributes to various Program Learning Outcomes related to the acquisition of knowledge, skills and their application in the field of statistical analysis.


 

On completion of this course you should be able to:

  1. Apply a range of multivariate statistical methods to data in psychology and the health sciences
  2. Use a statistical package such as SPSS to implement these statistical methods
  3. Interpret the statistical output produced by SPSS in implementing these statistical methods
  4. Write a report using APA format on the statistical analysis
  5. Interpret and explain the use of multivariate statistical techniques in the Psychology and Health Sciences literature


Overview of Learning Activities

Learning in this course will be facilitated by interactive discussion during lectures, use of SPSS in computer lab sessions and oral group presentations. Researching the Psychology and Health Sciences literature on the applications of advanced statistical techniques will enhance understanding of these techniques. Data analysis assignments will enable students to self-assess their own learning.


Overview of Learning Resources

 

Online notes, power point presentations on Canvas

Online Journal articles relevant to topics taught in Lectures

SPSS software.

http://rmit.libguides.com/mathstats


Overview of Assessment

 

Assessment Tasks:

Early Assessment Task: Revision Exercise
Review Exercise on past topics covered in MATH1279/1280, MATH1281/1282 to be done online in Week 1
Weighting = 10%
(CLOs 1-3)

Assessment Tasks 2 – 6: Data Analysis Reports (x5)
A data analysis report of 5 - 6 pages to be done and submitted every second week of the semester on topics covered in the previous week
Each of the reports will be assessed on all of the Course learning Outcomes listed in this Course Guide
Total weighting = 90% (5x18%)
(CLOs 1 – 5)