School of Health Sciences and Social Work
Dr Ngianga II Kandala (Shadrack)
- Qualifications: PhD in Social Statistics, University of Southampton, MSc in Social Statistics, University of Southampton, BSc Hons in Economics, University of Kinshasa, BSc Hons in Computer Sciences, University of Kinshasa
- Role Title: Senior Lecturer
- Address: St Michael's Building, White Swan Road, Portsmouth, PO1 2DT
- Telephone: +44 (0)23 9284 2847
- Email: Ngianga.firstname.lastname@example.org
- Department: School of Health Sciences and Social Work
- Faculty: Science
I joined the University of Portsmouth in 2015. I previously worked in the Faculty of medicine (Primary Care and Population Sciences, University of Southampton) as a Lecturer in Medical Statistics. I qualified in Social Statistics (Applied Statistics) from the University of Southampton. I graduated with a degree in Economics and Computer Sciences in 2005 and returned to academia in 2008 to study for an MSc in Social Statistics followed by a PhD at the University of Southampton.
"Dr Kandala believes that it is by using big data that we can answer many health related questions of today and of the future”
I have taught several modules including Quantitative methods in Public Health, Multilevel modelling, generalised linear models, analysis of discrete data, survival analysis, type of data and descriptive statistics. My current teaching includes:
- Studies design
- Epidemiological Methods
- Diagnostics and screening tests
- Type of data and descriptive statistics
- Analysis of continuous and categorical data
- Estimation (hypothesis testing and Confidence intervals)
- Sampling (Sample size and Power calculation)
I have been very active in undergraduate, postgraduate and professional public health training.
I have diverse research interests embracing the application of statistics in public health, maternal and child health, statistical modelling, generalised linear models, analysis of discrete data, multilevel modelling, survival analysis, epidemiological methods and longitudinal data analysis, and synthesis of research findings.