Biostatistics for Clinical and Public Health Research

Biostatistics for Clinical and Public Health Research

This short course introduces clinical and public health researchers to biostatistics as applied to public health and management studies.

Biostatistics is the science of describing, summarising and analysing health-related data. It is essential to understand biostatistics in order to design, conduct and interpret health-related research. The basic principles and methods used in biostatistics are covered in this short course, including the technical qualifications necessary for analysing and interpreting data on a descriptive and bivariate level.

Course outline

DAY 1

• Classification of data into types and study design
• Presenting data using graphs and summary statistics
• Data distribution and uncertainty measures in data analysis

DAY 2

• Comparing a group with a clinical cut-off
• Comparing the significance of differences between two or more groups (parametric and non-parametric methods)

DAY 3

• Evaluate the association of disease and exposure
• Determining the effect of one or multiple exposures on a disease
• Quantifying the risk of one or more exposures to a disease
• Power analysis

Attendees will be very briefly introduced to the computerised statistical package, SPSS. However, if you wish to become proficient in using SPSS, it is recommended that you register for the Introduction to Data Analysis: SPSS Without Tears course. The SPSS short course theory will be complemented by the use of applied examples and exercises to enhance understanding and facilitate development of practical skills. Completion of this Biostatistics for Clinical and Public Health Research short course (or equivalent training) is required prior to registering for the SPSS short course.

Who should attend?

This course is designed for medical doctors, nurses, physiotherapists, clinicians, epidemiologists, psychologists, pharmacists, biochemists and public health researchers who are interested in data analysis, report/journal article writing, report/journal article reviewing, and supervising researchers in the above areas.

Learning objectives

• Discuss the classification of data, various epidemiological studies, and the method of data collection for evaluating research questions in the concerned Epidemiological Studies
• Summarise data (using graphical display and descriptive statistics) that has been collected from the concerned populations
• Discuss the probability distributions for variables collected in public health studies (Application Level) and evaluate the sampling variability (uncertainty) in data analysis results
• Discuss the statistical significance of a hypothesis about the study population based on sample data (normality assumption holds) and evaluate the difference between two groups
• Formulate boundary values for parameters in the study population and evaluate the precision in its estimates based on sample data (normality assumption holds)
• Evaluate the difference between more than two groups based on sample data where data in each group follows the normal distribution
• Evaluate the difference between two or more groups when normality assumption does not hold or data is ordinal or discrete
• Explain the relationship between an outcome (continuous scale) and exposures and identify the truly independent exposures for the outcome of interest
• Evaluate the risk that an event (binary) will occur given a particular exposure, compared to the risk of the event occurring in the absence of that exposure
• Explain the relationship between a binary event and exposures and identify the truly independent exposures for the event of interest
• Evaluate the association between event (categorical) and exposure where either or both can have multiple categories

Course facilitator

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