Analysis of Variance and Regression
Duration
- One Semester or equivalent
Contact hours
- Swinburne Online: Fully online
Prerequisites
STA70006 Foundations of StatisticsAims and objectives
1. Apply and analyse data using multiple regression models
2. Interpret the results of multiple regression
3. Identify and explain the concepts of mediation and interaction (moderation) within multiple regression models
4. Apply and analyse data using analysis of variance (ANOVA) models
5. Explain the concept of interaction with ANOVA models and identify research problems where they can be usefully applied
6. Interpret results of ANOVA models
7. Interpret statistical analyses of data pertaining to theoretical and applied problems in psychology and health and write concise reports on the results of analyses in discipline-relevant style.
Courses with unit
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
This unit involves up to 150 hours of work including:
| Type [SOL] | Hours per week | Number of Weeks | Total |
| Face to Face Contact |
|
| N/A |
| Online Contact Collaborate sessions | 1 | 12 | 12 |
| Specified Learning Activities Readings Viewing videos, Tedtalks Self-check tests Online tests Webinars Interactive DB activities Online eLA-student interactions | 7 | 12 | 84 |
| Unspecified Learning Activities Independent study Assessment task preparation Reading up on current affairs relevant to topics | 4 | 12 | 48 |
| TOTAL |
|
| 144 hours/12.5cp |
Assessment
| Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
| Online topic tests (10) | Individual | 20% | 1, 2, 3, 4, 5, 6 |
| Assignment | Individual | 40% | 1, 2, 3, 4, 5, 6, 7 |
| Exam | Individual | 40% | 2, 3, 4, 6, 7 |
General skills outcomes
• Analysis Skills
• Problem Solving Skills
• Communication Skills
• Ability to tackle unfamiliar problems
• Ability to work independently
Content
o Review of Correlation and Simple Linear Regression
o Hypothesis testing
• Introduction to Multiple Regression Models
o Multiple regression
o Part and partial correlation
o Presentation of results
o Testing assumptions for regression
o Testing for interactions
• Analysis of Variance Models
o Introduction to the analysis of variance
o Single factor independent groups design
o Completely randomised factorial design
o Single factor within subjects design
o Mixed factorial design
Study resources
- References.