Effective experimentation : for scientists and technologists / Richard Boddy, Gordon Smith

Von:

Boddy, Richard [aut]

Mitwirkende(r):

Smith, Gordon [oth]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Verlag: Chichester, West Sussex, U.K : John Wiley, 2010Auflage: Online-AusgBeschreibung: Online-Ressource (1 online resource (xii, 256 p.)) : illISBN:

9781282653863
1282653865
9780470666647

Schlagwörter:

Andere physische Formen: 0470684607 | 9780470684603. | 1282653822 | Erscheint auch als: 978-0-470-68460-3 Druck-AusgabeDDC-Klassifikation:

507.27
507.2/7

LOC-Klassifikation:

Q182.3

Online-Ressourcen:

Zugang im Netz des KIT

Zusammenfassung: Effective Experimentation is a practical book on how to design and analyse experiments. Each of the methods are introduced and illustrated through real world scenario drawn from industry or research. Formulae are kept to a minimum to enable the reader to concentrate on how to apply and understand the different methods presented. The book has been developed from courses run by Statistics for Industry Limited during which time more than 10,000 scientists and technologists have gained the knowledge and confidence to plan experiments successfully and to analyse their data. Each chapter starts with an example of a design obtained from the authors' experience. Statistical methods for analysing data are introduced, followed, where appropriate, by a discussion of the assumptions of the method and effectiveness and limitations of the design. The examples have been chosen from many industries including chemicals, oils, building materials, textiles, food, drink, lighting, water, pharmaceuticals, electronics, paint, toiletries and petfoods. This book is a valuable resource for researchers and industrial statisticians involved in designing experiments. Postgraduates studying statistics, engineering and mathematics will also find this book of interest.Zusammenfassung: Effective Experimentation: For Scientists and Technologists -- Contents -- Preface -- 1 Why bother to design an experiment? -- 1.1 Introduction -- 1.2 Examples and benefits -- 1.2.1 Develop a better product -- 1.2.2 Which antiperspirant is best? -- 1.2.3 A complex project -- 1.3 Good design and good analysis -- 2 A change for the better - significance testing -- 2.1 Introduction -- 2.2 Towards a darker stout -- 2.3 Summary statistics -- 2.4 The normal distribution -- 2.5 How accurate is my mean? -- 2.6 Is the new additive an improvement? -- 2.7 How many trials are needed for an experiment? -- 2.8 Were the aims of the investigation achieved? -- 2.9 Problems -- 3 Improving effectiveness using a paired design -- 3.1 Introduction -- 3.2 An example: who wears the trousers? -- 3.3 How do we rate the wear? -- 3.4 How often do you carry out an assessment? -- 3.5 Choosing the participants -- 3.6 Controlling the participants -- 3.7 The paired design -- 3.8 Was the experiment successful? -- 3.9 Problems -- 4 A simple but effective design for two variables -- 4.1 Introduction -- 4.2 An investigation -- 4.3 Limitations of a one-variable-at-a-time experiment -- 4.4 A factorial experiment -- 4.5 Confidence intervals for effect estimates -- 4.6 What conditions should be recommended? -- 4.7 Were the aims of the investigation achieved? -- 4.8 Problems -- 5 Investigating 3 and 4 variables in an experiment -- 5.1 Introduction -- 5.2 An experiment with three variables -- 5.3 The design matrix method -- 5.4 Computation of predicted values -- 5.5 Computation of confidence interval -- 5.6 95% Confidence interval for an effect -- 5.7 95% Confidence interval for a predicted value -- 5.8 Sequencing of the trials -- 5.9 Were the aims of the experiment achieved? -- 5.10 A four-variable experiment -- 5.11 Half-normal plots -- 5.12 Were the aims of the experiment achieved?.PPN: PPN: 808918842Package identifier: Produktsigel: ZDB-26-MYL | ZDB-30-PAD | ZDB-30-PQE

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