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descriptive statistics, nonparmetrics; learn and share factoids about the problem to build situational awareness
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linear regression models, nonlinear regression models; estimate the relationships among your variables and create predictive models (machine learning); also use simulated data to create linear regression models and learn something new
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multivariate exploratory techniques; organize data into meaningful clusters, classify variables (reduce/relate variables), principal components & classification analysis
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process analysis, quality control, multivariate statistical process control; understand critical process parameters which impact critical quality attributes
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design of experiments, power analysis and interval estimation; experiment and discover; also use simulated data to execute virtual experiements
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tabulation options; everyone needs a summary table for their presentation to management