Designing Quantitative Experiments: Prediction Analysis
Autor John Wolbergen Limba Engleză Paperback – 6 mai 2010
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Specificații
ISBN-13: 9783642115882
ISBN-10: 3642115888
Pagini: 224
Ilustrații: XII, 208 p. 49 illus.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.32 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642115888
Pagini: 224
Ilustrații: XII, 208 p. 49 illus.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.32 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
Professional/practitionerCuprins
Statistical Background.- The Method of Least Squares.- Prediction Analysis.- Separation Experiments.- Initial Value Experiments.- Random Distributions.
Textul de pe ultima copertă
The method of Prediction Analysis is applicable for anyone interested in designing a quantitative experiment. The design phase of an experiment can be broken down into problem dependent design questions (like the type of equipment to use and the experimental setup) and generic questions (like the number of data points required, range of values for the independent variables and measurement accuracy). This book is directed towards the generic design phase of the process. The
methodology for this phase of the design process is problem independent and can be applied to experiments performed in most branches of science and technology. The purpose of the prediction analysis is to predict the accuracy of the results that one can expect from a proposed experiment. Prediction analyses can be performed using the REGRESS program which was developed by the author and can be obtained free-of-charge through the author's website. Many examples of prediction analyses are included in the book ranging from very simple experiments based upon a linear relationship between the dependent and independent variables to experiments in which the mathematical models are highly non-linear.
methodology for this phase of the design process is problem independent and can be applied to experiments performed in most branches of science and technology. The purpose of the prediction analysis is to predict the accuracy of the results that one can expect from a proposed experiment. Prediction analyses can be performed using the REGRESS program which was developed by the author and can be obtained free-of-charge through the author's website. Many examples of prediction analyses are included in the book ranging from very simple experiments based upon a linear relationship between the dependent and independent variables to experiments in which the mathematical models are highly non-linear.
Caracteristici
Enables scientists to apply the method to their specific problem Concentrates on the generic design phase of the experimental process Includes designing experiments with Bayesian estimators Includes supplementary material: sn.pub/extras