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A practical introduction to commonly used statistical methods, designed to increase the breadth of statistics skills. The emphasis is on the application of statistical techniques to solve problems involving real data.
The course is designed for students majoring in statistics, as well as students from other disciplines (e.g. biology, commerce, etc.) who want to increase the breadth of their statistical knowledgebase. We cover common statistical techniques such as the linear model and some of the analysis techniques based on statistical learning. Simple linear regression, multiple linear regression, analysis of variance, analysis of covariance, linear mixed models and multivariate statistics are introduced, with an emphasis on problem solving applied to real data. The computer package R is used, but no prior knowledge is assumed. Students on this course may also be interested in enrolling in STAT202/FORE224 Regression Modelling/Biometry 1B.
You will be able to:Use R in analysing data;understand commonly used statistical methods for analysis of univariate, and multivariate problems;know how to apply analysis techniques based on statistical learning methods;conduct statistical analyses using R;write lab reports in which data are analysed and computer output is interpreted
STAT101 or DATA101 or 15 points from 100-level MATH or EMTH (excluding MATH110)
FORE210, STAT220, FORE222, STAT222
Students must attend one activity from each section.
Crawley, Michael J;
The R book
Montgomery, Douglas C;
Design and analysis of experiments
John Wiley & Sons, Inc., 2017.
Zar, Jerrold H;
Prentice Hall, 2010.
These are on restricted loan in the Library.
General information for students
Domestic fee $802.00
International fee $4,563.00
* 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