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STAT403 Case Studies in Statistics

Application of advanced statistical methods through case studies

In real-world data analysis, a skilled statistician will utilize and adapt existing methodology to suit research goals at hand. This paper illustrates and provides background on a raft of specialized techniques in applied statistics, motivated by real case studies in statistics.

Paper title Case Studies in Statistics
Paper code STAT403
Subject Statistics
EFTS 0.1667
Points 20 points
Teaching period Semester 2 (On campus)
Domestic Tuition Fees (NZD) $1,206.91
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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STAT 401 or (STAT 270 and STAT 310)

Enrolments for this paper require departmental permission.
Pre-requisites are STAT401, or STAT270 and STAT310, or equivalent.


Teaching staff

Dr Tilman Davies

Professor Martin Hazelton

Paper Structure

Content and case studies form 5 to 6 modules drawn from:

  • Univariate smoothing
  • Time series
  • Multivariate smoothing
  • Spatial regression
  • Generalised additive models
  • Non-parametric testing
Teaching Arrangements

Lectures (2 per week); practicals/tutorials (1 per fortnight); student seminars (1 per fortnight).


Recommended reading:

A full course book/reader will be provided.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical thinking, Ethics, Information literacy, Research, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes

Students successfully completing this course will be able to  demonstrate the following:

  • Understanding of the relationship between theory and  application of specialized statistical techniques.
  • Identification of research question and ability to adapt  statistical methods to problems without standard solutions.
  • Ability to apply methodology and statistical computing to  analyse data using specialized techniques, and interpret results  in a logical manner.
  • Display autonomy and judgement in presenting results to  others, including non-scientists.

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Semester 2

Teaching method
This paper is taught On Campus
Learning management system