Multivariate Statistics for Understanding Complex Data
MULT : MULT42
This course teaches how to apply and interpret a variety of multivariate statistical methods to research and business data. The course emphasizes understanding the results of the analysis and presenting your conclusions with graphs.
Learn How To
- make sense of the math behind many multivariate statistical analyses
- reduce dimensionality with principal components analysis
- identify latent variables with exploratory factor analysis and factor rotation
- understand individual preferences with qualitative preference analysis
- explain associations among many categories with correspondence analysis
- finds patterns of association among different sets of continuous variables with canonical correlation analysis
- explain differences among groups in terms of many predictor variables through canonical discriminant analyses
- classify observations into groups with linear and quadratic discriminant analyses
- fit complex multivariate predictive models with partial least squares regression analysis.
Who Should Attend
Business analysts, social science researchers, marketers, and statisticians who want to use SAS to make sense of highly dimensional multivariate data
Prerequisites
Before attending this course, you should be familiar with statistical concepts such as hypothesis testing, linear models, and collinearity concepts in regression. You should have an understanding of the topics taught in Statistics 2: ANOVA and Regression or equivalent.
SAS Products Covered
SAS/STAT
Course Outline
Overview of Multivariate Methods
- examples of multivariate analyses
- matrix algebra concepts
- principal component analysis for dimension reduction
- factor analysis for latent variable measurement
- factor rotation
- plotting high-dimensional preference data
- mapping preferences to other characteristics
- understanding complex associations among categorical variables
- multivariate dimensions reduction for two sets of variables
- classification into groups
- linear discriminant analysis
- quadratic discriminant analysis
- empirical validation
- PLS for one target variable
- PLS for many targets
- PLS for predictive modeling
Live Class Schedule
Duration: 21 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.