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STAT342 Multivariate Methods

This is a paper in advanced statistical methods. Applications are widespread in the analysis of psychological, sociological and other types of behavioural data, including market research. Other areas of application include medicine, ecology, environmental science, geography and the biological sciences in general. Rather than concentrating on the mathematical aspects of the methods covered, the paper emphasises applications and data analysis through the use of the statistics package SPSS 22 and the SPSS add on AMOS 22 for confirmatory factor analysis. R may be used in some places.

Paper title Multivariate Methods
Paper code STAT342
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Second Semester
Domestic Tuition Fees (NZD) $851.85
International Tuition Fees (NZD) $3,585.00

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Prerequisite
36 200-level STAT points
Restriction
STAT 242
Schedule C
Arts and Music, Science
Notes
With approval from the Head of Department, the prerequisite 36 200-level STAT points may be waived for postgraduate students.
Eligibility
Undergraduate students in any of the subjects listed above will find this paper relevant. It is also a paper for anyone majoring in Statistics, and it presents methods that are not developed in other Statistics papers.

But, in addition, the paper could be a useful quantitative paper for graduate and research students in all areas. These students, who enrol in the paper as part of their research programme, will find they are already meeting the techniques in their own reading and data analysis. Note that this paper is restricted against STAT 242, which has the same lectures, but different assessment involving a project.
Contact
twang@maths.otago.ac.nz or jharraway@maths.otago.ac.nz
Teaching staff
Associate Professor John Harraway
Paper Structure
Main topics:
  • Multivariate analysis of variance
  • Fisher Discriminant function analysis
  • Logistic and multinomial regression for discrimination
  • Cluster analysis
  • Principal component analysis
  • Exploratory factor analysis
  • Confirmatory factor analysis using AMOS 22
  • Discrimination with logistic models if some categorical predictors
  • Canonical correlation analysis
  • Measures of distance
  • Methods of scaling and ordination
  • Correspondence analysis
  • Repeated measures
Teaching Arrangements
32 lectures and 12 tutorials
Textbooks
Recommended text: Multivariate Statistical Methods, a Primer, B.F.J. Manly (this book is on close reserve in the Science Library)

A course reader is available at the start of the second semester free of charge online (through the course resource page), and purchase of a hard copy through Uniprint is, therefore, optional.
Course outline
Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will develop an ability to explore and summarise large data sets.

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Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
L1 Tuesday 13:00-13:50 28-34, 36-41
Thursday 13:00-13:50 28-34, 36-41
Friday 13:00-13:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend one stream from
T1 Monday 14:00-14:50 29-34, 36-40
T2 Wednesday 14:00-14:50 29-34, 36-40
T3 Thursday 14:00-14:50 29-34, 36-40

This is a paper in advanced statistical methods. Applications are widespread in the analysis of psychological, sociological and other types of behavioural data, including market research. Other areas of application include medicine, ecology, environmental science, geography and the biological sciences in general. Rather than concentrating on the mathematical aspects of the methods covered, the paper emphasises applications and data analysis through the use of the statistics package SPSS 22 and the SPSS add on AMOS 22 for confirmatory factor analysis. R may be used in some places.

Paper title Multivariate Methods
Paper code STAT342
Subject Statistics
EFTS 0.1500
Points 18 points
Teaching period Second Semester
Domestic Tuition Fees (NZD) $868.95
International Tuition Fees (NZD) $3,656.70

^ Top of page

Prerequisite
36 200-level STAT points
Restriction
STAT 242
Schedule C
Arts and Music, Science
Notes
With approval from the Head of Department, the prerequisite 36 200-level STAT points may be waived for postgraduate students.
Eligibility
Undergraduate students in any of the subjects listed above will find this paper relevant. It is also a paper for anyone majoring in Statistics, and it presents methods that are not developed in other Statistics papers.

But, in addition, the paper could be a useful quantitative paper for graduate and research students in all areas. These students, who enrol in the paper as part of their research programme, will find they are already meeting the techniques in their own reading and data analysis. Note that this paper is restricted against STAT 242, which has the same lectures, but different assessment involving a project.
Contact
twang@maths.otago.ac.nz
Teaching staff
To be confirmed
Paper Structure
Main topics:
  • Multivariate analysis of variance
  • Fisher Discriminant function analysis
  • Logistic and multinomial regression for discrimination
  • Cluster analysis
  • Principal component analysis
  • Exploratory factor analysis
  • Confirmatory factor analysis using AMOS 22
  • Discrimination with logistic models if some categorical predictors
  • Canonical correlation analysis
  • Measures of distance
  • Methods of scaling and ordination
  • Correspondence analysis
  • Repeated measures
Teaching Arrangements
32 lectures and 12 tutorials.
Textbooks
Recommended text: Multivariate Statistical Methods, a Primer, B.F.J. Manly (this book is on close reserve in the Science Library)

A course reader is available at the start of the second semester free of charge online (through the course resource page), and purchase of a hard copy through Uniprint is, therefore, optional.
Course outline
View course outline for STAT 342
Graduate Attributes Emphasised
Communication, Critical thinking, Information literacy.
View more information about Otago's graduate attributes.
Learning Outcomes
Students who successfully complete the paper will develop an ability to explore and summarise large data sets.

^ Top of page

Timetable

Second Semester

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Other

Lecture

Stream Days Times Weeks
Attend
L1 Tuesday 13:00-13:50 28-34, 36-41
Thursday 13:00-13:50 28-34, 36-41
Friday 13:00-13:50 28-34, 36-41

Tutorial

Stream Days Times Weeks
Attend one stream from
T1 Monday 14:00-14:50 29-34, 36-40
T2 Wednesday 14:00-14:50 29-34, 36-40
T3 Thursday 14:00-14:50 29-34, 36-40