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    Essential analytical methods necessary for health-related research: data description, basic probability, confidence intervals, hypothesis testing, sample size calculation, epidemiological measures of association, and simple linear regression. A knowledge of basic algebra is recommended.

    This paper provides an introduction to the use of statistical methods to answer specific research questions in health-related areas.

    About this paper

    Paper title Biostatistics
    Subject Health Sciences
    EFTS 0.125
    Points 15 points
    Teaching period Semester 1 (On campus)
    Domestic Tuition Fees ( NZD ) $1,348.13
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    Limited to
    MHealSc, MPharm, MSc, PGDipHealSc, PGDipMLSc, PGDipSci, PGDipPharm, BMLSc(Hons)

    Suitable for students who are interested in upgrading their statistical skills for carrying out health-related quantitative research.

    Teaching staff
    Convenor and Lecturer: Jiaxu Zeng
    Paper Structure

    This paper covers the following main topics:

    1. Introduction to biostatistics
    2. Descriptive analysis
    3. Introduction to diagnostic testing
    4. Probability distributions
    5. Sampling distributions
    6. Confidence intervals
    7. Hypothesis testing
    8. Power and sample size calculation
    9. Introduction to epidemiological studies
    10. Critical appraisal of health research

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

    Graduate Attributes Emphasised
    Communication, Critical thinking, Research.
    View more information about Otago's graduate attributes.
    Learning Outcomes

    Students who successfully complete this paper will:

    • Perform basic statistical analyses to address simple research questions using a statistical software package (Stata)
    • Understand the principles behind basic statistical analyses
    • Understand how to interpret and present basic statistical analyses


    Semester 1

    Teaching method
    This paper is taught On Campus
    Learning management system

    Computer Lab

    Stream Days Times Weeks
    A1 Friday 10:00-11:50 9-12, 15-22


    Stream Days Times Weeks
    A1 Monday 14:00-15:50 9-13, 15-22
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