化学丛书：DATA ANALYSIS FOR CHEMISTRY
这是一本适合在校学生和一线工作者的丛书
The motivation for writing this book came from a number of sources. Clearly, one was the undergraduate students to whom we teach analytical chemistry, and who continually struggle with data analysis. Like scientists across the globe we stress to our students the importance of including uncertainties with any measurement result, but for at least one of us (JJG) we stressed this point without clearly articulating how. Conversations with many other teachers of science suggested JJG was not the exception but more likely the rule. The majority of lecturers understood the importance of data analysis but not always how best to teach it. In our school, like many others it seems, the local measurement guru has a good grasp of the subject, but the rest who teach other aspects of chemistry, and really only use data analysis as a tool in the laboratory class, understand it poorly in comparison. This is something we felt needed to be rectified, a second motivation.
In conversation between the pair of us we came to the conclusion that the problem was partly one of language. In writing this book we also came to the conclusion that another aspect of the problem was the uncertainty that arises from any discipline which is still evolving. Chemical data analysis, with aspects of metrology in chemistry and chemometrics, is certainly an evolving discipline where new and better ways of doing things are being developed. So this book tries to make data analysis simple, a sort of idiot’s guide, by (1) demystifying the language and (2) wherever possible giving unambiguous ways of doing things (recipes). To do this we took one expert (DBH) and one idiot (JJG) and whenever DBH stated what should be done JJG badgered him with questions such as, ‘‘What do you mean by that?,’’ ‘‘How exactly does one do that?,’’ ‘‘Can’t you be more definite?,’’ ‘‘What is a rule of thumb we can give the reader?’’ The end result is the compromise between one who wants essentially recipes on how to perform different aspects of data analysis and one who feels the need to give,
at the very least, some basic information on the background principles behind the recipes to be performed. In the end we both agree that for data analysis to be performed properly, like any science, it cannot be treated as a black box but for the novice to understand how to perform a specific test how to perform it must be unambiguous.
So who should use this book? Anybody who thinks they don’t really understand data analysis and how to apply it in chemistry. If you really do understand data analysis, then you may find the explanations in the book too simple and the scope too limited. We see this as very much an entry level book which is targeted at learning and teaching undergraduate data analysis. We have tried to make it easy for the reader to find the information they are seeking to perform the data analysis they think they need. To do this we have put the glossary at the beginning of the book with directions to where in the book a certain concept is located. We also add in this initial Readers’ Guide frequently asked questions (FAQs) with brief answers and directions to where more detailed answers are located, and a list of useful Microsoft Excel functions. Hopefully together these three sections will help you find out how to do things like when your lecturer tells you to ‘‘measure a calibration curve and then determine the uncertainty in your measurement of your unknown.’’ If after looking through this book, and then sitting down to work through the examples, you still are saying ‘‘How?’’ then we haven’t quite achieved our objective.
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