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Synopsis
This classic reference details methods for effectively analyzing non-standard or messy data sets. The authors introduce each topic with examples, follow up with a theoretical discussion, and conclude with a case study. They emphasize the distinction between design structure and the structure of treatments and focus on using the techniques with several statistical packages, including SAS, BMDP, and SPSS.
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Synopsis
This practical tool for statisticians offers techniques and methods for analyzing non-standard or messy data sets that arise from experimental design situations. Topics discussed include analysis of variance techniques, such as one- and two-way analyses of variance and multiple-comparison procedures. The book introduces each topic with several examples, follows up with a more theoretical discussion, and concludes with a case study. It emphasizes the distinction between design structure and the structure of treatments, and focuses on practical implementation, including computers, with several available statistical packages, including SAS, BMD and SPSS.
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Analysis of Messy Data Vol. 1 : Designed Experiments
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Analysis of Messy Data, Volume I: Designed Experiments
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Analysis of Messy Data, Volume I: Designed Experiments
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Analysis of Messy Data, Volume I: Designed Experiments
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Analysis of Messy Data, Volume I: Designed Experiments
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Analysis of Messy Data: Designed Experiments (Volume 1)
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Analysis of Messy Data, Volume I: Designed Experiments
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Analysis of Messy Data, Volume I: Designed Experiments
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