This course provides an introduction to the use of biostatistics in the fields of clinical research, epidemiology and public health. Topics include database entry and management, study design and hypothesis testing, descriptive statistics, correlational analyses, and analytical statistics (including parametric and non-parametric tests), as well as an introduction to univariate and multivariate regression methods. The course concludes with an introduction to scientific writing for the reporting of statistical findings based on international guidelines. Statistical analysis using SPSS is introduced via practical workshops in small tutorial groups and analyses of real-world research databases.
Who is this course for and why should I take it?
This course is intended for undergraduate and graduate students in allied health fields, research investigators and/or healthcare practitioners involved in medical or public health research. The course is also ideal for those in the academia who have an interest in developing or brushing up their data analysis skills for research and publications.
Acquiring knowledge and skills in statistical analysis is important for any practitioner that seeks to provide evidence-based solutions for real-world medical and public health challenges that require data analysis. Applied statistics is increasingly important across fields, including research, commercial sector (relating to i.e. health technology and administration, biotechnology and the pharmaceutical industry), non-governmental organizations and governmental public health work.
Attendees will join live online tutorial sessions using real world data examples. The course provides practical skills for conducting basic biostatical analyses in the fields of observational and interventional research studies, including clinical, epidemiologic and public health research. Upon course completion, attendees will have acquired the required knowledge and skills for conducting independently descriptive statistics, correlational analyses, and analytical statistics (including univariate and multivariate regression) using SPSS.
- Two of the top five fastest-growing skills for employment are related to data analytics. (LinkedIn, 2020)
- The top skills and skill groups that employers see rising in prominence in the lead up to 2025 include groups such as critical thinking and analysis. (WEF – Future of Jobs, 2020)
- Data analysis is the most in-demand skill since employers need to discern when patterns in data are meaningful, so that accurate and actionable conclusions can be drawn. (Forbes, 2017)