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Analyzing observed or measured data is an important step in applied sciences. The recent increase in computer capacity has resulted in a revolution both in data collection and data analysis. An increasing number of scientists, researchers and students are venturing into statistical data analysis; hence the need for more guidance in this field, which was previously dominated mainly by statisticians.
This handbook fills the gap in the range of textbooks on data analysis. Written in a dictionary format, it will serve as a comprehensive reference book in a rapidly growing field. However, this book is more structured than an ordinary dictionary, where each entry is a separate, self-contained entity. The authors provide not only definitions and short descriptions, but also offer an overview of the different topics. Therefore, the handbook can also be used as a companion to textbooks for undergraduate or graduate courses.
1700 entries are given in alphabetical order grouped into 20 topics and each topic is organized in a hierarchical fashion. Additional specific entries on a topic can be easily found by following the cross-references in a top-down manner. Several figures and tables are provided to enhance the comprehension of the topics and a list of acronyms helps to locate the full terminologies. The bibliography offers suggestions for further reading.
- No. of pages:
- © Elsevier Science 1994
- 30th September 1994
- Elsevier Science
- Hardcover ISBN:
- eBook ISBN:
@qu:My hope is that everyone who uses chemometrics will consider this to be an essential reference book - and will use it! @source:Journal of Chemometrics @qu:As with all books from this publisher, this one is beautifully bound and printed on the very highest quality paper. This is a fine desktop reference book. @source:Technometrics
Stanford, CA, USA
Milano Chemometrics and QSAR Research Group, Department of Environmental Sciences, University of Milan-Bicocca, Italy
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