Analysis of Variance and Regression
Duration
- 1 Semester or equivalent
Contact hours
- 4 Hours per Week
On-campus unit delivery combines face-to-face and digital learning. For Online unit delivery, learning is conducted exclusively online.
2023 teaching periods
Hawthorn Higher Ed. Semester 2 |
Hawthorn HOL Study Period 3 | |
---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Swinburne Online Teaching Period 1 |
Swinburne Online Teaching Period 2 | |
---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
Corequisites
NilAims and objectives
Students who successfully complete this unit will be able to:
1. Apply and analyse data using multiple regression models
Courses 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
Unit information in detail
- Teaching methods, assessment and content.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
Live Online Class |
2 |
12 |
24 |
On-Campus Class |
2 |
12 | 24 |
Online Learning activities |
3 |
12 |
36 |
Unspecified Activities Independent learning |
5.5 | 12 | 66 |
TOTAL |
|
| 150 hours |
Assessment
Types | Individual or Group task | Weighting | Assesses attainment of these ULOs |
Assignment | Individual | 40% | 1, 2, 3, 4, 5, 6, 7 |
Test | Individual | 40% | 2, 3, 4, 6, 7 |
Online Tests | Individual | 20% | 1, 2, 3, 4, 5, 6 |
Content
- A review of fundamentals
- 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.