Correspondence analysis is a powerful exploratory multivariate technique for categorical variables with many levels. It is a data analysis tool that characterizes associations between levels of two or more categorical variables using graphical representations of the information in a contingency table. It is particularly useful when categorical variables have many levels.
This presentation will give a brief introduction and overview of the use of correspondence analysis, including a review of chi square analysis, and examples interpreting both simple and multiple correspondence plots.
Note: This training is an exclusive benefit to members of the Statistically Speaking Membership Program and part of the Stat’s Amore Trainings Series. Each Stat’s Amore Training is approximately 90 minutes long.
About the Instructor
Dr. Thomson has a broad background in statistics, with specific emphasis on nutritional epidemiology as it relates to obesity. Her current projects include the design, implementation, and evaluation of nutrition and physical activity interventions targeting the prevention of obesity in adults and children, as well as identification of dietary patterns in nationally representative child data sets.
She has a PhD in mathematical statistics.
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