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Covers statistical methods for planning, conducting, and analyzing experiments to optimize a process. Topics include point estimation, confidence intervals, hypothesis testing, ANOVA models for 1, 2, and k-way classifications, multiple comparisons, randomized complete block designs, Latin square designs, and factorial designs. The course uses statistical software and emphasizes hands-on applications to data sets from a variety of settings.
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