Chemometrics : experimental design
著者
書誌事項
Chemometrics : experimental design
（Analytical chemistry by open learning）
Published on behalf of ACOL, London, by Wiley, 1991
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book is one of a series of easy-to-read, user-friendly texts written by some of the foremost lecturers in analytical chemistry in the UK. The texts are designed for training, continuing education and updating of all technical staff concerned with analytical chemistry. It is aimed at those interested in analytical chemistry and instrumental techniques who wish to study in a more flexible way than traditional institute attendance or to augment such attendance. This text concerns experimental design. Prat 1 provides a revision of some of the statistical methods used in experimental design and part 2 introduces randomization, replication and blocking, followed by some designs which have increasing degrees of complexity as far as blocking is concerned. These are some of the more fundamental areas of experimental design. Part 3 introduces designs with more than one factor (factorial designs) and mainly covers the two-level designs, which are useful for discovering whether variables are important. The emphasis here lies on discovering whether main effects and interactions are important.
Part 4 briefly covers fractional factorial designs which are very useful exploratory designs when it is not certain whether factors have any effect upon an experimental response. These designs have the advantage over complete factorial designs when a large number of factors has to be included in an initial investigation since they use a relatively small number of experimental runs. Part 5 covers response surface methodology.
目次
- Part 1 Basic statistics - a review: errors
- the t-test
- the f-test
- analysis of variance (ANOVA)
- summary. Part 2 Pinciples of experimental design: introduction
- running experiments in blocks
- latin squares. Part 3 Factorial designs and analysis: the factorial design (design with more than one factor)
- factorial design experiments at two levels
- estimation of effects
- use of replicates
- interpretation of effects. Part 4 Fractional factorials: redundancy of estimate
- half-fraction factorial designs
- generating factorial designs
- design resolution
- estimation, analysis and interpretation of effects. Part 5 Response surface methodology: response surfaces
- single-factor first-order model
- generalized least-squares matrix solution
- single-factor second-order model
- two-factor response surface designs
- steepest ascent
- second-order designs.
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