Multivariate Statistical Methods: Practical Research Applications

Duration: 3.0 days
Course fee: $2,040
EPTO units: 3
CEUs: 1.8

This course teaches how to apply a variety of multivariate statistical methods to research data.

Learn how to

perform multivariate analysis of variance (MANOVA) and multivariate regression analysis
perform canonical correlation and discriminant function analyses
perform principal components analysis
perform exploratory and confirmatory factor analysis
use structural equation modeling.

Who should attend

Statisticians, researchers, and data analysts with a strong statistical background

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Prerequisites

Before attending this course, you should

know how to create and manage SAS data sets
have experience performing a linear model analysis using the REG or GLM procedures of SAS/STAT software
have completed and mastered the material covered in the Statistics II: ANOVA and Regression course or completed a graduate-level course on general linear models.

Exposure to matrix algebra will enhance your understanding of the material. Some experience manipulating SAS data sets and producing graphs SAS software is also recommended.

Course Contents

Overview and Examples of Multivariate Methods

introduction and examples of multivariate statistics
review of univariate statistics
introduction to multivariate linear models
ODS Statistical Graphics in SAS 9.2

Analysis of Groups: Multivariate Analysis of Variance

factorial MANOVA
contrasts

More Multivariate Linear Models

multivariate multiple regression
canonical correlation

Classification Into Groups: Discriminant Analysis

canonical discriminant analysis
linear discriminant analysis
quadratic discriminant analysis
discriminant analysis and empirical validation

Variable Reduction and Extraction of Meaningful Factors

principal components analysis
exploratory factor analysis
Cronbach's coefficient alpha for scale reliability

Analysis of Structure Using the CALIS Procedure

introduction to structural equation models
confirmatory factor analysis
regression path models
structural equation models with latent variables
structural models with repeated measurements

Additional Data Topics

evaluating assumptions for multivariate analysis

Software

This course addresses SAS/STAT. This course also requires SAS/GRAPH software. A few demonstrations use SAS/IML software although it is not required for most of the activities in the course.

Course Materials

Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.

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Are there additional topics you'd like for this course to address? Would you like for this course to be offered at another training facility? Let us know by adding to our Interest List.

Course fee and EPTO units will differ for on-site training.

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