An interdisciplinary introduction to the basic principles of data analysis with an emphasis on application. Students are expected to apply these principles to data analysis in their respective areas of study. The applied focus is on the computerized application of summary statistics, one/two/multi-sample tests, linear models, association tests, randomness/normality tests, time series comparison, quality control charts and probability distributions as used across a variety of community and organizational settings. Other techniques may be added as appropriate for specific disciplines.