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PBH2002 · Foundations of biostatistics

Official Handbook

2026 Handbook6 credit pointsLevel 2School of Public Health and Preventive Medicine

Last checked: 23 Aug 2026 UTC

Overview

In this unit you will be introduced to the basic principles and methods used in biostatistics as applied to public health and clinical research. The key concepts covered will include the technical qualifications necessary for analysing and interpreting data on a descriptive and bivariate level. In this unit you will cover topics which include classification of health data, sampling methods;, study design, summarizing data using simple statistical methods and graphical presentation, sampling distributions, quantifying uncertainty in results from a sample, statistical distributions (normal and t-distribution), comparing two independent/paired groups using t-test (p-value) and confidence intervals, comparing more than two groups using Analysis of variance (ANOVA), non-parametric tests for comparing two or more groups when normality assumptions do not hold, assessing the association between an outcome and an exposure using the chi-squared test, and risk comparisons (RR & OR).

Areas of study: Health science Public health

Offerings

CampusTeaching periodMode
CaulfieldSecond semesterTeaching activities are on-campus (ON-CAMPUS)

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

#AssessmentTypeWeightHurdle
1Graphical data presentation assignment (1,500 words)Written25%
2Research hypothesis and evaluation (1,800 words)Written30%
3Online quiz (MCQ) (30 minutes)Quiz / Test10%
4Evaluation case study (2,000 words)Written35%

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

  1. Examine and explain the importance of biostatistics in public health studies
  2. Classify data into appropriate measurement types.
  3. Present data using relevant tables, graphical displays, summary statistics, and quantifiable uncertainty in study results.
  4. Formulate and evaluate research hypotheses into a statistical context in public health studies.
  5. Accurately interpret statistical methods and results reported in health publications.
  6. Analyse data output generated using a statistical software package.

Workload

6 hours of teacher directed study per week, this includes 3 hours of workshop and 3 hours of directed online student learning activities. 6 hours per week of self-directed study. Total per week = 12 hours

ActivityDuration
Lectures12 hours
Tutorials24 hours

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