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STAT110 Statistical Methods

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.

Paper title Statistical Methods
Paper code STAT110
Subject Statistics
EFTS 0.15
Points 18 points
Teaching period(s) Summer School (On campus)
Semester 1 (On campus)
Domestic Tuition Fees (NZD) $913.95
International Tuition Fees (NZD) $4,073.40

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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 and Megan Drysdale

Semester 1: Dr Phillip Wilcox and Megan Drysdale

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.

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Summer School

Teaching method
This paper is taught On Campus
Learning management system


Stream Days Times Weeks
L1 Monday 10:00-11:50 2-5, 7
Tuesday 10:00-11:50 2-7
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, 15-16, 18-22
A2 Monday 08:00-08:50 9-13, 15-16, 18-22
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, 15-22
D2 Thursday 08:00-08:50 9-13, 15-22