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The first course in statistics, no matter how "good" or "long" it is, typically covers inferential procedures which are valid only if a number of preconditions are satisfied by the data. For example, students are taught about regression procedures valid only if the true residuals are independent, homoscedastic, and normally distributed. But they do not learn how to check for indepen dence, homoscedasticity, or normality, and certainly do not learn how to adjust their data and/or model so that these assumptions are met. To help this student out I designed a second course, containing a collec...

An introduction to the theory and practical application of Bayesian statistics. It presents methods for assisting in the collection, summary and presentation of numerical data. A range of problems to challenge the reader are also included, making use of Minitab computational techniques.