Information and Decision Sciences

IDS 470 Multivariate Analysis

Credit hours 3 -Undergraduate 4 -Graduate
Catalog description Introduction to the structure and analysis of multivariate data. Emphasis on the multivariate normal model. Regression, tests concerning multivariate means, classification, discriminant analysis, principal components.
Key topics
  • Nature and Structure of Multivariate Data
  • Data Matrix
  • Descriptive Statistics: Means, standard deviations,covariances, correlations
  • Review of Simple and Multiple Linear Regression
  • Classification Basic Concepts of Classification Discriminant Analysis Logistic Regression Analysis
  • Principal Components Analysis
Prerequisites for this course IDS 371 and Math 205 (Advanced Mathematics for Business) or Math 310 (Applied Linear Algebra) or Math 320 (Linear Algebra I).
Course(s) for which this is a prerequisite IDS 471
Required course for None
Elective course for Selective course for IDS Majors
MBA Students with a Specialization/Concentration in Statistics
Frequency of offering Fall
Recent offerings, instructors, syllabi Fall 2005 Sclove
Planned offerings None
Cross-listings  
Comments None