The Multivariate Statistics for Understanding Complex Data training course teaches how to apply and interpret a variety of multivariate statistical methods to research and business data. Strong emphasis is on understanding the results of the analysis and presenting your conclusions with graphs.
By attending Multivariate Statistics for Understanding Complex Data workshop, delegates will learn 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
Familiar with statistical concepts such as hypothesis testing, linear models, and collinearity concepts in regression. Knowledge of ANOVA and Regression.
This Multivariate Statistics for Understanding Complex Data class is intended for Business analysts, social science researchers, marketers, and statisticians.