Data Analysis for Chemistry
An Introductory Guide for Students and Laboratory Scientists
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Data Analysis for Chemistry by D. Brynn Hibbert
Book DescriptionChemical data analysis, with aspects of metrology in chemistry and chemometrics, is an evolving discipline where new and better ways of doing things are constantly being developed. This book makes data analysis simple by demystifying the language and whenever possible giving unambiguous ways of doing things. Based on author D. Brynn Hibberts lectures on data analysis to undergraduates and graduate students, Data Analysis for Chemistry covers topics including measurements, means and confidence intervals, hypothesis testing, analysis of variance, and calibration models. The end result is a compromise between recipes of how to perform different aspects of data analysis, and basic information on the background principles behind the recipes to be performed. An entry level book targeted at learning and teaching undergraduate data analysis, Data Analysis for Chemistry makes it easy for readers to find the information they are seeking to perform the data analysis they think they need.
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Book DetailsISBN: 9780195162110
(235mm x 157mm x 18mm)
Imprint: Oxford University Press Inc
Publisher: Oxford University Press Inc
Publish Date: 3-Nov-2005
Country of Publication: United States
Books By Author D. Brynn Hibbert
Quality Assurance in the Analytical Chemistry Laboratory, Paperback (April 2007)
This book takes the reader through all aspects of quality assurance, from the statistical basics and quality control tools to becoming accredited to international standards. The latest understanding of concepts such as measurement uncertainty, metrological traceability and interlaboratory studies are explained for a working chemist or her customer.
Data Analysis for Chemistry, Hardback (October 2005)» View all books by D. Brynn Hibbert
Based on D Brynn Hibbert's lectures on data analysis to undergraduates and graduate students, this book covers topics including measurements, means and confidence intervals, hypothesis testing, analysis of variance, and calibration models. It is meant as an entry level book targeted at learning and teaching undergraduate data analysis.
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