Analysis of Variance and Regression

STA20006 12.5 Credit Points Hawthorn, Online

Duration

  • 1 Semester

Contact hours

  • 4 Hours per Week

Corequisites

Nil

Courses with unit

BA-HSC1 Bachelor of Health Science
BA-HSCPROF Bachelor of Health Science (Professional)
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
 
Previously titled Analysis of Variance 

Aims and objectives

This unit introduces the fundamental statistical areas of research design and linear models. It examines how Analysis of Variance (ANOVA) and multiple regression can be used to analyse experimental and observational research data from a range of research designs. 
 
Students who successfully complete this unit will be able to:  
1.     Apply analysis of variance (ANOVA) models to experimental data from a range of research designs
2.     Identify and analyse examples of interaction in research data
3.     Explain the concepts of mediation and moderation with respect to research design and analysis
4.     Analyse data using multiple regression models
5.     Interpret the results of ANOVA and regression models and write a concise report
 
2018 
This unit will introduce students to fundamental statistical areas of research design and linear models. It examines how multiple regression and Analysis of Variance (ANOVA) can be used to analyse experimental and observational research using a variety of research designs.


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