Practical Methods for Data Analysis
Basic exploratory data analysis with business examples. Data summaries, multivariate data, time series, multiway tables. Techniques include graphical display, transformation, outlier identification, cluster analysis, smoothing, regression, robustness. Departmental credit allowed for only one of 403 and 503. Prerequisite: B A 500 or QMETH 500 or equivalent or permission of instructor. Offered: jointly with QMETH 503.