STAT403 Case Studies in Statistics

Overview

Application of advanced statistical methods through case studies

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

About this paper

Prerequisite

STAT 401 or (STAT 270 and STAT 310)

Eligibility

Enrolments for this paper require departmental permission.
Pre-requisites are STAT 401, or STAT 270 and STAT 310, or equivalent.

Contact

tilman.davies@otago.ac.nz

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).

Textbooks

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

Timetable