STAT446-16S1 (C) Semester One 2016

Generalised Linear Models

15 points

Details:
Start Date: Monday, 22 February 2016
End Date: Sunday, 26 June 2016
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 6 March 2016
  • Without academic penalty (including no fee refund): Sunday, 22 May 2016

Description

Generalised Linear Models

How do you analyse data that does not fit the standard methods such as ANOVA and regression? How do you deal with data that are very non-normal, are counts rather than measurements, are correlated and have interdependencies? In this course we introduce you to the very useful toolbox of Generalised Linear Models (GLMs). This is a natural progression from understanding ANOVA, regression and multivariate techniques. We will learn about the general framework for GLMs, and how to use GLMs for analysing data. We will introduce you to the package R, and will use this software throughout the course. Some background in statistical analysis methods is necessary, and useful courses to have completed are STAT220, STAT212 and STAT315. No experience in R is necessary.


For a full list of Honours courses, please refer to the School of Mathematics and Statistics Honours Booklet Mathematics and Statistics Honours Booklet

Learning Outcomes

  • The Courses will:

  • introduce generalised linear models
  • introduce advanced data analysis techniques including mixed effects models, repeated measures and additive models
  • introduce the use of the statistics computer package R
  • give you experience in writing scientific and technical reports

    You will be able to:

  • describe and conduct appropriate statistical modeling techniques for almost any dataset
  • be able to interpret the model results in such a way that a non-user of statistics can understand
  • use R competently
  • write a scientific and technical report

Prerequisites

Subject to approval of the Head of School.

Course Coordinator

Jennifer Brown

Lecturer

Alasdair Noble

Assessment

The course is assessed by four assignments, each worth 25% (in total 100%). There is no final exam.

Assignments give you practice in analysing data and presenting results in a written report.  You will be expected to use R for analysis.

The assignments will involve time and effort, but are an opportunity for you to learn not only statistical modeling techniques, but to develop your writing skills.  We discuss how to write a report during lectures, and provide considerable support especially for students who have not  had the chance to develop their scientific writing skills.

Textbooks / Resources

Recommended Reading:

Crawley, M.J. 2005. Statistics : an introduction using R. 327pp.
Crawley, M.J. 2007. The R book. 942pp.
Faraway, J.J. 2005.  Linear models in R.  229pp.
Faraway, J.J. 2006.  Extending the linear models with R.  301pp.

These are on High Demand in the EPS Library.

Indicative Fees

Domestic fee $913.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All STAT446 Occurrences

  • STAT446-16S1 (C) Semester One 2016
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