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About this product
- DescriptionThe first course in statistics, 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 rmally distributed. But they do t learn how to check for indepen- dence, homoscedasticity, or rmality, and certainly do t 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- tion of statistical diagstics and prescriptions necessary for the applied statistician so that he can deal with the realities of inference from data, and t merely with the kind of classroom problems where all the data satisfy the assumptions associated with the technique to be taught. At the same time I realized that I was writing a book for a wider audience, namely all those away from the classroom whose formal statistics education ended with such a course and who apply statistical techniques to data.
- Author(s)Albert Madansky
- PublisherSpringer-Verlag New York Inc.
- Date of Publication22/01/2012
- Series TitleSpringer Texts in Statistics
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Note128 black & white tables, biography
- Weight486 g
- Width156 mm
- Height234 mm
- Spine17 mm
- Format DetailsTrade paperback (US)
- Edition StatementSoftcover reprint of the original 1st ed. 1988
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