George A. Milliken, Dallas E. Johnson
Analysis of Messy Data Volume 1 (eBook, PDF)
Designed Experiments, Second Edition
113,95 €
113,95 €
inkl. MwSt.
Sofort per Download lieferbar
57 °P sammeln
113,95 €
Als Download kaufen
113,95 €
inkl. MwSt.
Sofort per Download lieferbar
57 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
113,95 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
57 °P sammeln
George A. Milliken, Dallas E. Johnson
Analysis of Messy Data Volume 1 (eBook, PDF)
Designed Experiments, Second Edition
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei
bücher.de, um das eBook-Abo tolino select nutzen zu können.
Hier können Sie sich einloggen
Hier können Sie sich einloggen
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since t
- Geräte: PC
- mit Kopierschutz
- eBook Hilfe
- Größe: 7.24MB
Andere Kunden interessierten sich auch für
- George A. MillikenAnalysis of Messy Data, Volume III (eBook, PDF)52,95 €
- Real-World Evidence in a Patient-Centric Digital Era (eBook, PDF)47,95 €
- Azizur RahmanScientific Data Analysis with R (eBook, PDF)52,95 €
- Akihiro HirakawaModern Dose-Finding Designs for Cancer Phase I Trials: Drug Combinations and Molecularly Targeted Agents (eBook, PDF)48,95 €
- Esa UusipaikkaConfidence Intervals in Generalized Regression Models (eBook, PDF)65,95 €
- Mark ChangAdaptive Design Theory and Implementation Using SAS and R (eBook, PDF)41,95 €
- Rafael A. IrizarryIntroduction to Data Science (eBook, PDF)57,95 €
-
-
-
A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since t
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 674
- Erscheinungstermin: 2. März 2009
- Englisch
- ISBN-13: 9781420010152
- Artikelnr.: 42765609
- Verlag: Taylor & Francis
- Seitenzahl: 674
- Erscheinungstermin: 2. März 2009
- Englisch
- ISBN-13: 9781420010152
- Artikelnr.: 42765609
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
George A. Milliken, Dallas E. Johnson
The Simplest Case: One-Way Treatment Structure in a Completely Randomized
Design Structure with Homogeneous Errors. One-Way Treatment Structure in a
Completely Randomized Design Structure with Heterogeneous Errors.
Simultaneous Inference Procedures and Multiple Comparisons. Basics for
Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots,
Repeated Measures, and Combinations. Matrix Form of the Model. Balanced
Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced
Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way
Treatment Structures with Unequal Subclass Numbers. Using the Effects Model
to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass
Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal
Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with
Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way
Treatment Structures with Missing Treatment Combinations. Using the Effects
Model to Analyze Two-Way Treatment Structures with Missing Treatment
Combinations. Case Study: Two-Way Treatment Structure with Missing
Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment
Structures. Case Study: Three-Way Treatment Structure with Many Missing
Treatment Combinations. Random Effects Models and Variance Components.
Methods for Estimating Variance Components. Methods for Making Inferences
about Variance Components. Case Study: Analysis of a Random Effects Model.
Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for
Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type
Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of
Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied.
Case Studies: Complex Examples Having Repeated Measures. Analysis of
Crossover Designs. Analysis of Nested Designs. Appendix. Index.
Design Structure with Homogeneous Errors. One-Way Treatment Structure in a
Completely Randomized Design Structure with Heterogeneous Errors.
Simultaneous Inference Procedures and Multiple Comparisons. Basics for
Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots,
Repeated Measures, and Combinations. Matrix Form of the Model. Balanced
Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced
Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way
Treatment Structures with Unequal Subclass Numbers. Using the Effects Model
to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass
Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal
Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with
Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way
Treatment Structures with Missing Treatment Combinations. Using the Effects
Model to Analyze Two-Way Treatment Structures with Missing Treatment
Combinations. Case Study: Two-Way Treatment Structure with Missing
Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment
Structures. Case Study: Three-Way Treatment Structure with Many Missing
Treatment Combinations. Random Effects Models and Variance Components.
Methods for Estimating Variance Components. Methods for Making Inferences
about Variance Components. Case Study: Analysis of a Random Effects Model.
Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for
Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type
Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of
Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied.
Case Studies: Complex Examples Having Repeated Measures. Analysis of
Crossover Designs. Analysis of Nested Designs. Appendix. Index.
The Simplest Case: One-Way Treatment Structure in a Completely Randomized
Design Structure with Homogeneous Errors. One-Way Treatment Structure in a
Completely Randomized Design Structure with Heterogeneous Errors.
Simultaneous Inference Procedures and Multiple Comparisons. Basics for
Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots,
Repeated Measures, and Combinations. Matrix Form of the Model. Balanced
Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced
Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way
Treatment Structures with Unequal Subclass Numbers. Using the Effects Model
to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass
Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal
Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with
Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way
Treatment Structures with Missing Treatment Combinations. Using the Effects
Model to Analyze Two-Way Treatment Structures with Missing Treatment
Combinations. Case Study: Two-Way Treatment Structure with Missing
Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment
Structures. Case Study: Three-Way Treatment Structure with Many Missing
Treatment Combinations. Random Effects Models and Variance Components.
Methods for Estimating Variance Components. Methods for Making Inferences
about Variance Components. Case Study: Analysis of a Random Effects Model.
Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for
Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type
Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of
Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied.
Case Studies: Complex Examples Having Repeated Measures. Analysis of
Crossover Designs. Analysis of Nested Designs. Appendix. Index.
Design Structure with Homogeneous Errors. One-Way Treatment Structure in a
Completely Randomized Design Structure with Heterogeneous Errors.
Simultaneous Inference Procedures and Multiple Comparisons. Basics for
Designing Experiments. Multilevel Designs: Split-Plots, Strip-Plots,
Repeated Measures, and Combinations. Matrix Form of the Model. Balanced
Two-Way Treatment Structures. Case Study: Complete Analyses of Balanced
Two-Way Experiments. Using the Means Model to Analyze Balanced Two-Way
Treatment Structures with Unequal Subclass Numbers. Using the Effects Model
to Analyze Balanced Two-Way Treatment Structures with Unequal Subclass
Numbers. Analyzing Large Balanced Two-Way Experiments Having Unequal
Subclass Numbers. Case Study: Balanced Two-Way Treatment Structure with
Unequal Subclass Numbers. Using the Means Model to Analyze Two-Way
Treatment Structures with Missing Treatment Combinations. Using the Effects
Model to Analyze Two-Way Treatment Structures with Missing Treatment
Combinations. Case Study: Two-Way Treatment Structure with Missing
Treatment Combinations. Analyzing Three-Way and Higher-Order Treatment
Structures. Case Study: Three-Way Treatment Structure with Many Missing
Treatment Combinations. Random Effects Models and Variance Components.
Methods for Estimating Variance Components. Methods for Making Inferences
about Variance Components. Case Study: Analysis of a Random Effects Model.
Analysis of Mixed Models. Case Studies of a Mixed Model. Methods for
Analyzing Split-Plot Type Designs. Methods for Analyzing Strip-Plot Type
Designs. Methods for Analyzing Repeated Measures Experiments. Analysis of
Repeated Measures Experiments When the Ideal Conditions Are Not Satisfied.
Case Studies: Complex Examples Having Repeated Measures. Analysis of
Crossover Designs. Analysis of Nested Designs. Appendix. Index.