2021 – 2025
Undergraduate
Survival Analysis · STAT3035
Kaplan–Meier estimation, hazard functions, design of experiments, model checking, multiple events and frailty. I developed the course material, practicals and assessments.
Teaching
Senior Lecturer (since November 2025), School of Statistics and Actuarial Science, University of the Witwatersrand. Teaching at Wits since April 2018.
Statistics courses taught by Dr Raeesa Manjoo-Docrat at the University of the Witwatersrand, including survival analysis and spatial statistics.
I teach undergraduate and postgraduate courses in applied statistics, spatial statistics, survival analysis and statistical programming. I try to connect theory with practice, and R is central to how I teach.
Courses
2018 – 2025
Postgraduate
Spatial Statistics · STAT7006 / STAT4107
Spatial random variables, testing for spatial autocorrelation, variograms, and spatial prediction with simple and ordinary kriging. Separate curricula for GIS and Honours students.
2020 – 2025
Undergraduate
Mathematical Statistics II · STAT2005
Transformations of random variables, bivariate transformations, order statistics and hypothesis testing. I developed the course material, practicals and assessments.
2025
Undergraduate
Introduction to Spatial Statistics · STAT3037
Spatial data, autocorrelation, spatial sampling and applications, designed for the GIS professional degree.
2019
Undergraduate
Applied Statistical Modelling · STAT3032
Time series analysis, regression-based methods, ARIMA and the Box–Jenkins methodology, and spectral analysis. Coordinated labs with four tutors.
2018
Short course
R Short Course
Basic statistical modelling in R. I helped develop the content, lectured and ran the practical sessions.
Teaching philosophy
I want students to think critically, solve practical problems and understand statistical ideas deeply. My classes combine theory with real-world applications through R, R Shiny apps, live coding and group work, in an environment where every student feels able to take part.
I adapt my approach to each audience. For service courses I simplify concepts without losing depth, I take applied students through both the theory and the software, and I give mathematically strong students harder problems.
Innovations I have introduced include:
- Posit (RStudio) Cloud for real-time feedback on students’ scripts during online learning
- R Shiny applications that let students explore statistical concepts without prior coding experience
- A pre-semester R bootcamp (2022) to close gaps left by online learning
- Group R Shiny projects for applied, collaborative learning
- Sentiment analysis of students’ written feedback to better understand their learning experience