Waubonsee Community College

Statistics for experimenters, an introduction to design, data analysis, and model building, George E.P. Box, William G. Hunter, J. Stuart Hunter

Label
Statistics for experimenters, an introduction to design, data analysis, and model building, George E.P. Box, William G. Hunter, J. Stuart Hunter
Language
eng
Bibliography note
Includes bibliographical references and index
Illustrations
illustrations
Index
index present
Literary Form
non fiction
Main title
Statistics for experimenters
Nature of contents
bibliography
Oclc number
3327353
Responsibility statement
George E.P. Box, William G. Hunter, J. Stuart Hunter
Series statement
Wiley series in probability and mathematical statistics
Sub title
an introduction to design, data analysis, and model building
Summary
Introduces the philosophy of experimentation and the part that statistics play in experimentation. Emphasizes the need to develop a capability for "statistical thinking" by using examples drawn from actual case studies
Table Of Contents
1. Science and statistics -- Part I: Comparing two treatments -- 2. Use of external reference distribution to compare two means -- 3. Random sampling and the Declaration of Independence -- 4. Randomization and blocking with paired comparisons -- 5. Significance tests and confidence intervals for means, variances, proportions, and frequencies -- Part II: Comparing more than two treatments -- 6. Experiments to compare k treatment means -- 7. Randomized blocks and two-way factorial designs -- 8. Design with more than one blocking variables -- Part III: Measuring the effects of variables -- 9. Empirical modeling -- 10. Factorial designs at two levels -- 11. More applications of factorial designs -- 12. Fractional factorial designs at two levels -- 13. More applications of fractional factorial designs -- Part IV: Building models and using them -- 14. Simple modeling with least squares (regression analysis -- 15. Response surface methods -- 16. Mechanistic model building -- 17. Study of variation -- 18. Modeling dependence: time series
Content
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