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    Descriptive statistics, probability distributions, estimation, hypothesis testing, regression, analysis of count data, analysis of variance and experimental design. Sampling and design principles of techniques to build on in the implementation of research studies.

    This is a paper in statistical methods for students from any of the sciences, including students studying biological sciences, social sciences or sport science, as well as those studying mathematics and statistics. The paper provides an introduction to the use of statistical methods for the description and analysis of data, use of computer software to carry out data analysis, and the interpretation of the results of statistical analyses for a range of research studies.

    About this paper

    Paper title Statistical Methods
    Subject Statistics
    EFTS 0.15
    Points 18 points
    Teaching period(s) Summer School (On campus)
    Semester 1 (On campus)
    Domestic Tuition Fees ( NZD ) $981.75
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    STAT 115, (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. 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

    Summer School Course Co-ordinator: Dr Tilman Davies

    Semester 1 Course Coordinator: Associate Professor Matthew Schofield

    Paper Structure

    The paper covers:

    • Data: where does it come from and how should we collect it?
    • Probability
    • Binomial and normal distributions
    • Sampling distributions
    • Confidence Intervals and estimation
    • Hypothesis testing and power
    • Contingency tables for categorical data
    • Analysis of variance
    • Regression including simple linear and multiple linear with confounding discussion
    Teaching Arrangements

    Four 1-hour lectures per week, plus cafeteria-style (voluntary attendance) tutorials each week for assistance with course material and exercises.


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

    Graduate Attributes Emphasised

    Interdisciplinary perspective, Scholarship, Communication, Critical thinking, Information literacy.
    View more information about Otago's graduate attributes.

    Learning Outcomes

    Demonstrate awareness of and proficiency in the basics of objective statistical data analysis.


    Summer School

    Teaching method
    This paper is taught On Campus
    Learning management system


    Stream Days Times Weeks
    L1 Monday 10:00-11:50 2-7
    Tuesday 10:00-11:50 2-5, 7
    Wednesday 10:00-11:50 2-7
    Thursday 10:00-11:50 2-7

    Semester 1

    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 9-13, 15-21
    A2 Monday 08:00-08:50 9-13, 15-21
    AND one stream from
    B1 Tuesday 10:00-10:50 9-13, 15-22
    B2 Tuesday 08:00-08:50 9-13, 15-22
    AND one stream from
    C1 Wednesday 10:00-10:50 9-13, 15-22
    C2 Wednesday 08:00-08:50 9-13, 15-22
    AND one stream from
    D1 Thursday 10:00-10:50 9-13, 15-16, 18-22
    D2 Thursday 08:00-08:50 9-13, 15-16, 18-22
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