Statistical Principles for the Design of Experiments :: Applications to Real Experiments.
Focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis in various disciplines.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | , |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge :
Cambridge University Press,
2012.
|
| Schriftenreihe: | Cambridge series on statistical and probabilistic mathematics.
|
| Schlagworte: | |
| Online-Zugang: | DE-862 DE-863 |
| Zusammenfassung: | Focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis in various disciplines. |
| Beschreibung: | 1 online resource (584 pages) |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781139570695 1139570692 9781139020879 1139020870 9781139568883 1139568884 113957244X 9781139572446 |
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| 880 | 0 | |6 505-00/(S |a Cover -- Statistical Principles for the Design of Experiments -- SERIES EDITOR -- Title -- Copyright -- Contents -- Preface -- Part I Overture -- 1 Introduction -- 1.1 Why a statistical theory of design-- 1.2 History, computers and mathematics -- 1.3 The influence of analysis on design -- 1.4 Separate consideration of units and treatments -- 1.5 The resource equation -- 2 Elementary ideas of blocking: the randomised complete block design -- 2.1 Controlling variation between experimental units -- 2.2 The analysis of variance identity -- 2.3 Estimation of variance and the comparison of treatment means -- 2.4 Residuals and the meaning of error -- 2.5 The random allocation of treatments to units -- 2.6 Practical choices of blocking patterns -- 3 Elementary ideas of treatment structure -- 3.1 Choice of treatments -- 3.2 Factorial structure -- 3.3 Models for main effects and interactions -- 3.4 The analysis of variance identity -- 3.5 Interpretation of main effects and interactions -- 3.6 Advantages of factorial structure -- 3.7 Treatment effects and treatment models -- 4 General principles of linear models for the analysis of experimental data -- 4.1 Introduction and some examples -- 4.2 The principle of least squares and least squares estimators -- 4.2.1 Some examples -- 4.3 Properties of least squares estimators -- 4.3.1 The estimation of σ2 -- 4.4 Overparameterisation, constraints and practical solution of least squares equations -- 4.4.1 Practical constraints on parameter values -- 4.4.2 A more complex example of the use of constraints -- 4.5 Subdividing the parameters -- extra SS -- 4.5.1 An example where different orders of fitting produce different SS -- 4.6 Distributional assumptions and inferences -- 4.7 Contrasts, treatment comparisons and component SS -- 4.7.1 Examples of the use of contrasts. | |
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| author | Mead, R. (Roger) |
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| contents | 1. Introduction -- 2. Elementary ideas of blocking: the randomised complete block design -- 3. Elementary ideas of treatment structure -- 4. General principles of linear models for the analysis of experimental data -- 5. Experimental units -- 6. Replication -- 7. Blocking and control -- 8. Multiple blocking systems and cross-over designs -- 9. Multiple levels of information -- 10. Randomisation -- 11. Restricted randomisation -- 12. Experimental objectives, treatments and treatment structures -- 13. Factorial structure and particular forms of effects -- 14. Fractional replication -- 15. Incomplete block size for factorial experiments -- 16. Quantitative factors and response functions -- 17. Multifactorial designs for quantitative factors -- 18. Split-unit designs -- 19. Multiple experiments and new variation -- 20. Sequential aspects of experiments and experimental programmes -- 21. Designing useful experiments. |
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| illustrated | Not Illustrated |
| indexdate | 2025-04-11T08:41:05Z |
| institution | BVB |
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| series | Cambridge series on statistical and probabilistic mathematics. |
| series2 | Cambridge Series in Statistical and Probabilistic Mathematics |
| spelling | Mead, R. (Roger) https://id.oclc.org/worldcat/entity/E39PBJrKRm6FTxVgG44Yf7hj4q http://id.loc.gov/authorities/names/n82114129 Statistical Principles for the Design of Experiments : Applications to Real Experiments. Cambridge : Cambridge University Press, 2012. 1 online resource (584 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Cambridge Series in Statistical and Probabilistic Mathematics Print version record. Focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis in various disciplines. Includes bibliographical references and index. 1. Introduction -- 2. Elementary ideas of blocking: the randomised complete block design -- 3. Elementary ideas of treatment structure -- 4. General principles of linear models for the analysis of experimental data -- 5. Experimental units -- 6. Replication -- 7. Blocking and control -- 8. Multiple blocking systems and cross-over designs -- 9. Multiple levels of information -- 10. Randomisation -- 11. Restricted randomisation -- 12. Experimental objectives, treatments and treatment structures -- 13. Factorial structure and particular forms of effects -- 14. Fractional replication -- 15. Incomplete block size for factorial experiments -- 16. Quantitative factors and response functions -- 17. Multifactorial designs for quantitative factors -- 18. Split-unit designs -- 19. Multiple experiments and new variation -- 20. Sequential aspects of experiments and experimental programmes -- 21. Designing useful experiments. Experimental design. http://id.loc.gov/authorities/subjects/sh85046441 Research Design https://id.nlm.nih.gov/mesh/D012107 Plan d'expérience. MATHEMATICS Probability & Statistics General. bisacsh REFERENCE Research. bisacsh Experimental design fast Gilmour, S. G. http://id.loc.gov/authorities/names/n2012049712 Mead, A. (Andrew) https://id.oclc.org/worldcat/entity/E39PBJmXH7RvcXxJyjr4vCXDbd http://id.loc.gov/authorities/names/n2012049717 has work: Statistical Principles for the Design of Experiments (Text) https://id.oclc.org/worldcat/entity/E39PCFCy6qDr7ww8xmhP46BvRC https://id.oclc.org/worldcat/ontology/hasWork Print version: 9780521862141 Cambridge series on statistical and probabilistic mathematics. http://id.loc.gov/authorities/names/n96064948 505-00/(S Cover -- Statistical Principles for the Design of Experiments -- SERIES EDITOR -- Title -- Copyright -- Contents -- Preface -- Part I Overture -- 1 Introduction -- 1.1 Why a statistical theory of design-- 1.2 History, computers and mathematics -- 1.3 The influence of analysis on design -- 1.4 Separate consideration of units and treatments -- 1.5 The resource equation -- 2 Elementary ideas of blocking: the randomised complete block design -- 2.1 Controlling variation between experimental units -- 2.2 The analysis of variance identity -- 2.3 Estimation of variance and the comparison of treatment means -- 2.4 Residuals and the meaning of error -- 2.5 The random allocation of treatments to units -- 2.6 Practical choices of blocking patterns -- 3 Elementary ideas of treatment structure -- 3.1 Choice of treatments -- 3.2 Factorial structure -- 3.3 Models for main effects and interactions -- 3.4 The analysis of variance identity -- 3.5 Interpretation of main effects and interactions -- 3.6 Advantages of factorial structure -- 3.7 Treatment effects and treatment models -- 4 General principles of linear models for the analysis of experimental data -- 4.1 Introduction and some examples -- 4.2 The principle of least squares and least squares estimators -- 4.2.1 Some examples -- 4.3 Properties of least squares estimators -- 4.3.1 The estimation of σ2 -- 4.4 Overparameterisation, constraints and practical solution of least squares equations -- 4.4.1 Practical constraints on parameter values -- 4.4.2 A more complex example of the use of constraints -- 4.5 Subdividing the parameters -- extra SS -- 4.5.1 An example where different orders of fitting produce different SS -- 4.6 Distributional assumptions and inferences -- 4.7 Contrasts, treatment comparisons and component SS -- 4.7.1 Examples of the use of contrasts. |
| spellingShingle | Mead, R. (Roger) Statistical Principles for the Design of Experiments : Applications to Real Experiments. Cambridge series on statistical and probabilistic mathematics. 1. Introduction -- 2. Elementary ideas of blocking: the randomised complete block design -- 3. Elementary ideas of treatment structure -- 4. General principles of linear models for the analysis of experimental data -- 5. Experimental units -- 6. Replication -- 7. Blocking and control -- 8. Multiple blocking systems and cross-over designs -- 9. Multiple levels of information -- 10. Randomisation -- 11. Restricted randomisation -- 12. Experimental objectives, treatments and treatment structures -- 13. Factorial structure and particular forms of effects -- 14. Fractional replication -- 15. Incomplete block size for factorial experiments -- 16. Quantitative factors and response functions -- 17. Multifactorial designs for quantitative factors -- 18. Split-unit designs -- 19. Multiple experiments and new variation -- 20. Sequential aspects of experiments and experimental programmes -- 21. Designing useful experiments. Experimental design. http://id.loc.gov/authorities/subjects/sh85046441 Research Design https://id.nlm.nih.gov/mesh/D012107 Plan d'expérience. MATHEMATICS Probability & Statistics General. bisacsh REFERENCE Research. bisacsh Experimental design fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85046441 https://id.nlm.nih.gov/mesh/D012107 |
| title | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_auth | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_exact_search | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_full | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_fullStr | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_full_unstemmed | Statistical Principles for the Design of Experiments : Applications to Real Experiments. |
| title_short | Statistical Principles for the Design of Experiments : |
| title_sort | statistical principles for the design of experiments applications to real experiments |
| title_sub | Applications to Real Experiments. |
| topic | Experimental design. http://id.loc.gov/authorities/subjects/sh85046441 Research Design https://id.nlm.nih.gov/mesh/D012107 Plan d'expérience. MATHEMATICS Probability & Statistics General. bisacsh REFERENCE Research. bisacsh Experimental design fast |
| topic_facet | Experimental design. Research Design Plan d'expérience. MATHEMATICS Probability & Statistics General. REFERENCE Research. Experimental design |
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