The most popular course on multiple regression in Africa

Monday 26th – Friday 30th August (5 days) – Johannesburg, South Africa

Monday 14th – Friday 18th October (5 days) – Cape Town, South Africa


Every researcher wants to be sure that observed associations are valid. After using bi-variate tests (such as chi-squared test, t-test, ANOVA, etc) to demonstrate association between two variables of interest, the next critical question is whether those associations are valid i.e. whether they can in fact be explained by other variables (confounding) or study methodology (bias). In order words, in strengthening causal inference, it is vital to eliminate the role of confounding and bias. Multiple regression remains the most well-known approach for controlling for confounding and estimating independent effects. 
Multiple regression models are used to determine risk factors after adjusting for confounding. They are also commonly used to build models for predicting an outcome. Therefore, researchers should be able to build, understand and interpret multiple regression models.


This course teaches participants to fit multiple regression models and estimate measures of effect. Simple and multiple regression models for crude and adjusted effects will be covered. Three types of regression models will be covered – linear, quantile and logistic regression.
The course uses a fine blend of didactic lectures, group exercises for every session and two project reports that simulate real life scenarios. After the course, participants will be able to understand the link between bi-variate tests and regression model, for example, the link between t-test and linear regression and chi-squared test and logistic regression. They will be able to build causal or predictive models and interpret the outputs. They will be able to adjust for confounders and estimate independent effects, thereby strengthening causal inference in their research.
The course is taught using Stata. So, it is a pre-requisite that the participants have at least one of the following:

  • Have attended CESAR’s level 1 course: Data Analysis and Management Course using Stata
  • Have previous experience working with Stata
  • Have no previous experience with Stata but can conduct bi-variate tests using another statistical package.

Course Contents

Day 1

Review of bi-variate tests and measures of effect
Bias, confounding and interaction
How to control for confounders: design and analysis
Application of regression models
Linear regression models for continuous outcomes
T-test, ANOVA, correlation and linear regression

Day 2

Interpretation of ANOVA and linear regression outputs
Simple and multiple linear regression
Model fitting and variable selection
Assumptions of linear regression and post-regression diagnostics

Day 3

When linear regression assumptions are not met
Quantile regression
Fitting simple and multiple models
First project report

Day 4

Logistic regression models for binary outcomes
Odds, log odds, and logistic regression
Chi-squared test simple logistic regression
Multiple logistic regression

Day 5

Model fitting and variable selection
Assumptions of linear regression and post-regression diagnostics
Second project report

Registration information


All 5 days only R14000.00 (Excl. VAT) per delegate
Price Includes
Course attendance
Full refreshments: lunch
Welcome tea
Two breaks for tea including pastries
Course lecture notes and training manual
Complimentary parking
Certificate of attendance


Five days

Who Should Attend?

Research Analysts
Data analysts
Programme managers
Postgraduate students
Market Researchers
Clinical and Medical researchers
Government Practitioners


For more details about our services contact
Tel: +27 11 403 1411