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PUBH725 Applied Biostatistics 1 - Fundamentals

Introduction to the use of statistical methods in health sciences research. Descriptive and simple inferential statistics for discrete, continuous and right-censored data. Introduction to linear regression.

This distance-taught paper will introduce students to the use of statistical methods in health sciences research and is highly recommended for all students that want and/or need to analyse quantitative data. Students will learn the theory needed to perform basic descriptive analysis and to begin to understand appropriate statistical methods to test quantitative questions. The paper has a strong applied component, and students will learn how the foundations of biostatistics apply to public health. Topics covered include: descriptive statistics, hypothesis testing and introduction to study design. Students will learn to use Stata, a leading statistical software package in health sciences research. For this paper, students must have a computer with an Internet connection and be computer literate.

Paper title Applied Biostatistics 1 - Fundamentals
Paper code PUBH725
Subject Public Health
EFTS 0.125
Points 15 points
Teaching period 1st Non standard period (2 May 2022 - 11 July 2022) (Distance learning)
Domestic Tuition Fees (NZD) $1,469.00
International Tuition Fees (NZD) $5,443.63
International Tuition Fees (NZD) $5,443.63

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HASC 413
Limited to
MA, MAppSc, MClinPharm, MHealSc, MMLSc, MPH, MPharm, MPHC, MSc, DPH, PGDipAppSc, PGDipArts, PGDipHealSc, PGDipMLSc, PGDipPharm, PGDipSci, PGCertPH
(i) PGCertPHC and PGDipPHC students require approval from the Board of Studies in Primary Health Care to enrol for this paper. (ii) This paper runs for the first half of first semester. (iii) Please note that this paper will be offered in the second half of the first semester.
Students who have completed an undergraduate degree in any discipline or recognised equivalent

Department of Preventive and Social Medicine, Dunedin campus:

Teaching staff

Paper Co-convenors: Associate Professor Gabrielle Davie (Lead convenor)
Professor Robin Turner
Dr Jimmy Zeng

Paper Structure


  1. Introduction to Biostatistics
  2. Descriptive Statistics and Graphical Summaries
  3. Sampling Distributions
  4. Confidence Intervals
  5. Hypothesis Testing and Sample Size
  6. Analysis for epidemiological studies

Assessment Structure

  1. Participation and contribution: 10% of the marks for this paper will derive from your contribution to Zoom sessions and discussion forums. The marks will not be awarded for the correctness of your contributions, but for making an effort to engage with the question at hand and to use the reading and other learning that you have done to progress the discussion.
  2. Assignment 1: This assignment, worth 40% of the mark for the paper, assesses your ability to perform descriptive statistics and to report summaries on high-quality tables and plots. It will cover material up until the end of week 3.
  3. Assignment 2: This assignment, worth 50% of the mark for the paper, will assess your learning on material covered in the course, with an emphasis on materials covered from week 4.
Teaching Arrangements
  1. Compulsory webinar sessions: Tuesday afternoons, 4pm-6pm.
  2. Block Week (zoom webinars): Monday 2nd May, Tuesday 3rd May, Wednesday 4th May, 4pm-6pm.

Altman, Douglas G (1990) Practical Statistics for Medical Research.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking, Information literacy, Research, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will be able to
  • Demonstrate an understanding of types of data and appropriate descriptive statistics and graphical summaries
  • Apply skills in simple data analysis methods and measures of precision and interpreting the results
  • Demonstrate and apply understanding of the statistical issues in research design and data analysis

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1st Non standard period (2 May 2022 - 11 July 2022)

Teaching method
This paper is taught through Distance Learning
Learning management system