Analysis of Variance and Regression
Duration
- 1 Semester
Contact hours
- 4 Hours per Week
Prerequisites
Corequisites
NilCourses with unit
BB-HSCBUS Bachelor of Health Science / Bachelor of Business
BB-HSCMCMN Bachelor of Health Science / Bachelor of Media and Communication
BB-HSCSCI Bachelor of Health Science / Bachelor of Science
Aims and objectives
Students who successfully complete this unit will be able to:
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. Identify and explain the concept of interaction with ANOVA models
6. Interpret results of ANOVA models
7. Write concise reports of analyses
Unit information in detail
- Teaching methods, assessment, general skills outcomes and content.
Teaching methods
This unit involves up to 150 hours of work including:
1. Hawthorn on-campus delivery:
| Type | Hours per week | Number of Weeks | Total |
| Face to Face Contact Lecture Tutorial |
2 2 |
12 12 |
24 24 |
| Online Contact |
|
| N/A |
| Specified Learning Activities (textbook exercises , quizzes) | 3 | 12 | 36 |
| Unspecified Learning Activities (Independent study, assignment preparation, revision) |
|
| 66 |
| TOTAL |
|
| 150 hours/12.5cp |
NOTE: 48 contact hours (or the online equivalent is essential for teaching these statistical methods.
2. Hawthorn Online and OUA delivery
| Type | Hours per week | Number of Weeks | Total |
| Face to Face Contact Lecture Tutorial |
|
| N/A
|
| Online Contact |
|
| N/A |
| Specified Learning Activities Lecture recordings Staff facilitated discussion boards Other Activities (textbook exercises , quizzes, structured activities) |
2 2 3 |
12 12 12 |
24 24 36 |
| Unspecified Learning Activities (Independent study, assignment preparation , revision) |
|
| 66 |
| TOTAL |
|
| 150 hours/12.5cp |
3. Swinburne on line (SOL) delivery:
| Type | 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 |
| 2 Assignments | Individual | 30% | 1,2,,3,4 |
| Examination | Individual | 50% | 1,2,3,4 |
To achieve a pass in this unit of study, students must achieve a mark of at least 40% on the final exam.
| 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
During this unit students will receive feedback on the following key generic skills:
• Analysis Skills
• Problem Solving Skills
• Communication Skills
• Ability to tackle unfamiliar problems
• Ability to work independently
Content
· Entering data into SPSS
· Hypothesis testing
Introduction to Multiple Regression· Multiple regression
· Part and partial correlation
· Presentation of results
· Testing assumptions for regression
· Testing for interactions
Analysis of Variance
· Introduction to the analysis of variance
· Single factor independent groups design
· Completely randomised factorial design
· Single factor within subjects design
· Mixed factorial design
• Review of Correlation and Simple Linear Regression
• Hypothesis testing
Introduction to Multiple Regression Models
• Multiple regression
• Part and partial correlation
• Presentation of results
• Testing assumptions for regression
• Testing for interactions
Analysis of Variance Models
• Introduction to the analysis of variance
• Single factor independent groups design
• Completely randomised factorial design
• Single factor within subjects design
• Mixed factorial design
Study resources
- Reading materials.