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 touse 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. 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 INDICE: TOC: Part I : Basic Concepts.- Introduction.- Statistical Background.-Least Squares.- Prediction Analysis.- Part II : Analysis of Experiments.- Experiments with a Single Independent Variable.- Experiments with Several Independent Variables.- Experiments with Several Dependent Variables.
- ISBN: 978-3-642-11588-2
- Editorial: Springer
- Encuadernacion: Rústica
- Páginas: 200
- Fecha Publicación: 01/04/2010
- Nº Volúmenes: 1
- Idioma: Inglés