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Short Learning Programme
Regression and ANOVA methods
The reason why the NWU wishes to offer the course is to give individuals the necessary tools to understand, analyse and interpret data on a specific research topic. There is an ever increasing demand for individuals being able to perform quantitative analysis. Statistics plays an integral role in quantitative research, therefore by enhancing statistical knowledge the quality of research outputs will improve.

Purpose of the course:

This short course aims to equip participants with the skills necessary to understand, analyse and interpret the statistical output obtained from regression and ANOVA analyses produced by computer software in order to answer specific research questions. The participant will gain deeper insight into the application of regression and ANOVA methods.

Admission requirements:

Admission requirements: 
Learning assumed to be in place: 
National Senior Certificate or an equivalent NQF level 4 qualification

Course outcomes and assessment criteria :

Course outcomes and the associated assessment criteria: 

Study Unit


Assessment Criteria


After completion of this course, participants will:

  1. Demonstrate informed knowledge and clear understanding of regression, ANOVA and ANCOVA methods applied in quantitative research.
  2. Demonstrate an ability to select and apply appropriate regression, ANOVA and ANCOVA methods within different research studies and interpret the statistical software output from these methods.  
  3. Demonstrate an ability to report results in a reliable, accurate and an ethical manner.

Participant will be assessed on the following criteria:

  1. Discuss the role of regression, ANOVA and ANCOVA methods in addressing various research problems in different research studies.
  2. Explain the different inferential statistical procedures related to regression, ANOVA and ANCOVA methods.
  3. Discuss and analyse the residuals obtained from fitting regression, ANOVA and ANCOVA models to data.
  4. Explain the assumptions underlying regression and ANOVA methods and be able to diagnose violations of these assumptions.
  5. Apply remedial measures to address violations of the assumptions of regression and ANOVA methods.
  6. Calculate and interpret main factorial and interaction effects in a two-way ANOVA model.
  7. Calculate and interpret post-hoc tests for one-way and two-way ANOVA methods, as well as for ANCOVA methods.
  8. Discuss and implement dummy variables as a substitute for qualitative regressors in regression models.
  9. Identify the most suitable technique for a given quantitative research problem.
  10. Calculate and display appropriate regression, ANOVA or ANCOVA statistics, graphs and statistical inferential techniques using appropriate computer software.
  11. Interpret the output from the regression, ANOVA and ANCOVA methods and be able to report these results in a statistically sound and an ethical manner.


Informal class interaction.
Method of assessment: 
Attendance and participation in short course activities.

Additional information

Mode of delivery: 
Target group: 
Postgraduate students busy with research, researchers or any person who would like to enhance his or her statistical knowledge relating to regression and ANOVA methods.
Contact us
Prof JS Allison
Telephone number: 
018 299 2571