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Pharmaceutical Experimental Design and Interpretation

Autor N. Anthony Armstrong
en Limba Engleză Paperback – 5 sep 2019
Completely revised and updated, Pharmaceutical Experimental Design and Interpretation, Second Edition explains the major methods of experimental design and evaluation such as multivariate, sequential, and principal components analysis. With new sections on neural networks, artificial intelligence, fractional designs, and optimization techniques, this source will prove invaluable to anyone involved in the design and execution of pharmaceutical research studies and the interpretation of study data.
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Specificații

ISBN-13: 9780367391188
ISBN-10: 036739118X
Pagini: 256
Dimensiuni: 156 x 234 x 18 mm
Greutate: 0.45 kg
Ediția:2nd edition
Editura: CRC Press
Colecția CRC Press

Public țintă

Academic and Professional Practice & Development

Cuprins

Introduction to Experimental Design. Comparison of Mean Values. Non-parametric Treatments. Correlation and Regression. Multivariate Methods. Cluster and Discrimination Analysis. Principal Components and Factor Analysis. Sequential Analysis. Factorial Design of Experiments. Model-dependent Optimization and Response Surface Methodology. Model-independent Optimization. Experimental Designs for Mixtures Appendix 1: Statistical Tables. Appendix 2: Computer Programs in BASIC and MINITAB Commands. Appendix 3: Sequential Analysis Grids. Appendix 4: Matrices

Descriere

Completely updated, this new edition explains the major methods of experimental design and evaluation such as multivariate, sequential, and principal components analysis. It offers new sections on neural networks, artificial intelligence, fractional designs, and optimization techniques. Taking a practice-orientated approach, it employs current case studies to illustrate important concepts, so as to deliver a clear understanding of statistical approaches without repeating information from older statistics textbooks. It supplies appendices on statistical tables, computer programs in BASIC and MINITAB Commands, sequential analysis grids, and matrices.