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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
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Biculturally competent and confident
Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.
Engaged with the community
Students will have observed and understood a culture within a community by reflecting on their own performance and experiences within that community.
Globally aware
Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.
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.
Jennifer Brown
Crawley, Michael J; The R book ; 2nd ed; Wiley, 2012.
Montgomery, Douglas C; Design and analysis of experiments ; Ninth edition; John Wiley & Sons, Inc., 2017.
Zar, Jerrold H; Biostatistical analysis ; 5th ed; Prentice Hall, 2010.
These are on restricted loan in the Library.
Library portalLEARN
Domestic fee $897.00
International fee $5,188.00
* 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 .