02409 Multivariate Statistics

Practical information
Lecture notes
Additional notes
Exercises
Exam
Suggested supplementary reading

Practical information

Lecture notes

• "Multivariate Statistics - An introduction 8. ed.", Bjarne Kjær Ersbøll & Knut Conradsen, 2012. ISBN: 978-87-643-1091-7

Additional notes

• Collection of problems for written exercises, here.
• SAS-examples on the examples from the book, here.
• Statistical table in PS or PDF.

Solutions to problems for written exercises will be available on CampusNet as the course proceeds.

Exercises

• Lecture 1
  • SAS intro
  Today's exercise will aim at making yourself familiar with the SAS interface and syntax. All information on what to do is stated in the SAS intro.
• Lecture 2
  1. SAS intro 2
  2. Problem 8 and E20 from the collection of written exercises found on Campusnet. See tip in the SAS intro.
• Lecture 3
  • Exercise on Principal Component Analysis (PCA).
• Lecture 4
  • Complete exercises on PCA by means of SAS.
  • Problem 2 from Exam 9. December 2011 (found on CampusNet).
  • Assignment on Factor Analysis (found on CampusNet).
• Lecture 5
  1. Problem 4 from Exam 9. December 2011 (found on CampusNet).
  2. Exercise on Canonical Correlation Analysis (CCA).
  3. Analysis of bitemporal satellite data.
• Lecture 6
  1. Finish Exercise on CCA. Note: you can download the SAS code for the second exercise on CampusNet.
  2. SAS Exercises on Discriminant Analysis. Note: you can find documentation for PROC DISCRIM here.
  3. Problem E9 from the collection of written exercises (exercises.pdf on CampusNet).
  4. Problem E44 from the collection of written exercises.
• Autumn Break
• Lecture 7
  1. Finish the SAS exercises on Discriminant Analysis.
  2. Assignment on Canonical Discriminant Functions.
  3. Problem 3, questions 3.3, 3.4, 3.5, 3.6 from Exam 9. December 2011.
  4. Problem 10 (in Collection of Exercises), by hand.
  5. Problem 12 (in Collection of Exercises), questions 1, 2, and the part of 4 corresponding to 1, 2 (use the SAS procedure glm).
• Lecture 8
  1. Finish Problem 12 (in Collection of Exercises).
  2. SAS Exercise on the Generalized Linear Model (GLM)
  3. Problem 13 (in Collection of Exercises).
  4. Problem E19 (in Collection of Exercises).
• Lecture 9
  1. Chemical Process GLM exercise
  2. Problem 4 from Exam 7. december 2010
  3. Problem 3 from Exam 8. december 2009. Use SAS yourselves to solve this problem.
  4. Problem 17 (in Collection of Exercises).
  5. Problem 53 (in Collection of Exercises).
• Lecture 10
  1. Finish Problem 17 and 53 (in Collection of Exercises). You can download Exercise17.sas from CN to import the data.
  2. Problems 1 and 6, Exam 9. Dec. 2011.
  3. Problem 8, Exam 11. Dec. 2007.
  4. Assignment on Hotellings T-square.
• Lecture 11
  1. Problem 8 from exam 10/12 2001. Note: the problem is based on example 5.4 in the book -- not 6.4!
  2. Problem 2 from exam 5/1 2001.
  3. Problem 5 from exam 7/12 2010.
  4. Problem 6 from exam 8/12 2009.
  5. Problem 4 from exam 9/12 2008.
  6. Problem 3 from exam 9/12 2011.
• Lecture 12
  1. Exam 7/12 2010, all problems except 6 and 7. Note: you may have solved some problems before.
  2. Exam 9/12 2011, all problems. Note: you may have solved some problems before.
• Lecture 13
  1. Exam 11/12 2012.

SAS tips and tricks

A few tips on how to make SAS easier to work with can be found here.

Useful links

• PROC CANDISC explained using Iris dataset: http://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_candisc_sect019.htm
• Interpreting PROC GLM output: http://www.ats.ucla.edu/stat/sas/output/sas_glm_output.htm
• Interpreting PROC REG output: http://www.ats.ucla.edu/stat/sas/output/reg.htm
• Using the MANOVA option for PROC GLM.
• Annotated output of MANOVA: http://www.ats.ucla.edu/stat/sas/output/SAS_manova.htm.

Exam

4 hours written examination (multiple choice). The exam questions can include questions regarding the interpretation of SAS-output.

Suggested supplementary reading

• “Applied Multivariate Statistical Analysis”, 6th ed., Richard A. Johnson and Dean W. Wichern, Prentice Hall, 2007.
• “Foundations of Statistical Analyses and Applications with SAS”, Michael Falk, Frank Marohn, Bernward Tewes, Birchäuser Verlag, 2002.