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    A paper for students in health-related subjects, in particular nutrition, food science, epidemiology, exercise science, psychology, and the health sciences. Topics covered include the nature of random variation, the concepts of bias and confounding, study design, data description including risks and odds, binomial and normal distributions, estimation, hypothesis testing, regression, the control of confounders, critical appraisal, and the analysis of variance.

    Biostatistics (statistics applied in the health sciences) is a vital tool in the mission to improve health and well-being for all people. STAT 115 provides an introduction to the core principles and methods of biostatistics. In this paper you will gain an understanding of how statistics is used to answer research questions: how to look for patterns in data and how to test hypotheses about disease causation and prevention and improvement in wellbeing. The program "R" will be used throughout the paper for data summary and statistical analysis. The understanding and skills gained in STAT 115 can be a starting point for a career in biostatistics or can be used to assist understanding of research in other disciplines including epidemiology, physiology, anatomy, human nutrition, sports science and psychology.

    About this paper

    Paper title Introduction to Biostatistics
    Subject Statistics
    EFTS 0.15
    Points 18 points
    Teaching period Semester 2 (On campus)
    Domestic Tuition Fees ( NZD ) $981.75
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    STAT 110, (BSNS 102 or BSNS 112), QUAN 101
    Schedule C
    Arts and Music, Science

    Suitable for students of all disciplines with an interest in the quantitative analysis of data, especially in the health sciences.

    There are no formal mathematical or statistical prerequisites for this paper, but students who have not done mathematics or statistics at NCEA Level 3 are encouraged to make use of the online and tutorial resources available as part of the paper.


    Teaching staff

    Professor Martin Hazelton

    Professor Katrina Sharples

    Megan Drysdale

    Paper Structure

    Main topics:

    • Basic measures for describing data
    • Introduction to statistical program "R"
    • Introduction to probability
    • Binomial and normal distributions
    • Estimation and confidence intervals
    • Hypothesis testing
    • Categorical data analysis
    • Simple linear regression
    • Regression procedures and the control of confounding
    • The analysis of variation (ANOVA)
    • Statistical issues in study design and critical appraisal of research
    Teaching Arrangements

    Four lectures per week.

    Cafeteria-style (voluntary attendance) tutorials each week for assistance with course material and exercises.


    There is no set text. Copies of all lecture slides are available at the start of the course either in electronic or paper form.

    Graduate Attributes Emphasised
    Interdisciplinary perspective, Lifelong learning, Scholarship, Critical thinking, Information literacy.
    View more information about Otago's graduate attributes.
    Learning Outcomes
    Students who successfully complete the paper will demonstrate awareness of and proficiency in the basics of objective statistical data analysis.


    Semester 2

    Teaching method
    This paper is taught On Campus
    Learning management system


    Stream Days Times Weeks
    Attend one stream from
    A1 Monday 10:00-10:50 29-35, 37-42
    A2 Monday 08:00-08:50 29-35, 37-42
    AND one stream from
    B1 Tuesday 10:00-10:50 29-35, 37-42
    B2 Tuesday 08:00-08:50 29-35, 37-42
    AND one stream from
    C1 Wednesday 10:00-10:50 29-35, 37-42
    C2 Wednesday 08:00-08:50 29-35, 37-42
    AND one stream from
    D1 Thursday 10:00-10:50 29-35, 37-42
    D2 Thursday 08:00-08:50 29-35, 37-42
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