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Data Analysis for Chemistry: An Introductory Guide for Students and Laboratory Scientists
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About the Author
D. Brynn Hibbert is at University of New South Wales. J. Justin Gooding is at University of New South Wales.
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Product details
Paperback: 192 pages
Publisher: Oxford University Press; 1 edition (October 27, 2005)
Language: English
ISBN-10: 9780195162110
ISBN-13: 978-0195162110
ASIN: 0195162110
Product Dimensions:
9.1 x 0.5 x 6 inches
Shipping Weight: 13.1 ounces (View shipping rates and policies)
Average Customer Review:
4.5 out of 5 stars
7 customer reviews
Amazon Best Sellers Rank:
#1,335,173 in Books (See Top 100 in Books)
In this book by Hibbert and Gooding some of the best things from other classical textbooks are nicely combined.In Miller & Miller's "Statistics for Analytical Chemistry" the explanations are very accessible (somewhat basic and incomplete) but the software approach is missing. In Gardiner's "Statistical Analysis Methods for Chemists" the explanations are kind of complicated (but very complete) but the software approach is present even on the title.The advantage in Hibbert and Gooding's "Data Analysis for Chemistry" consists in how briefly and simply the fundamentals of the statistical analysis of data and errors usually found on the chemical sciences are treated via the omnipresent MS Excel. Very useful are the chapters on hypothesis testing (specially normality and outliers) and calibration (specially outliers and residuals, the abuses of R² and limits of detection).Its disadvantage is precisely the lack of insight, which makes it a great book for a first course on Analytical Chemistry but a bad one for a Physical Chemistry course (where things are no longer straight lines, model comparison is of prime importance and the implications of the hypothesis testing are more profound).So, in conclusion: A) buy it if you're a chemistry student (it will save you a lot of work and will make a nice foundation for what's comming); B) don't buy it if you're a professor (better yet, undust your copies of Miller, Gardiner, Draper's "Applied Regression Analysis" and buy a book on data analysis with Excel).
Don't blame me, the authors called it that in their preface!Although this fine little self study guide uses chem as examples, the authors could have just as easily be describing "shocking of undergrad" experiments in psych, the migration of the great tufted flying lizard, or the distribution of bosons vs. the likelihood of nuclear war. In short, the book really is a GREAT little guide to ANOVA, t-tests, r-squared and all the applied stats you have forgotten long ago, in ANY field.It is wonderful both pedagogically and as a reference. It begins, amazingly, WITH the glossary, and then points to the sections where the terms are further explained. Then, it gives FAQ's, and shows where to find more detailed answers. If you're getting the impression that these guys are reader friendly, you've got it!Other really great reviews on this and other texts rightfully point out the 3 bears-- there are MANY texts on stats that are too big, too small, but not just right. What they sometimes miss is cost: a lot of those other big boys cost from $40 to $140+. This little beauty can be had for $9 used. Some of the formulas are grad level, but ALL of the explanations are advanced High School math level and certainly undergrad.LOTs of charts, examples, questions with solutions and detailed discussions about what does and doesn't work in journal articles and reports out in the real juried world. These authors have a been there done that practicality that is rarely found in the too dry or too sparse world of data crunching.Highly recommended as a refresher, helper, study guide, reference and most of all KEEPER to turn back to again and again to check on formulas, uses, meanings and best practices in disclosing and reporting on uncertainty while detailing your results and conclusions. Only point of disagreement with the authors: NOT FOR DUMMIES. They just meant they tried to make it understandable, intuitive and easy to grasp. Otherwise, grad students, teachers, etc. will find it enlightening and fun, especially in chem, but also in any other application of ANOVA-like crunching. BTW, VERY Excel friendly.Speaking of, if you ARE in Chemistry, and don't mind $50 well spent for over 700 pages, you can't go wrong with Billo: Excel for Chemists, with CD-ROM: A Comprehensive Guide. It is the "next step" in applying all those formulas from Hibbert and Gooding in the present volume and is a great complement because Billo doesn't go into the theory and Hibbert doesn't go as much into Excel, including of course Excel 2010. Make SURE you get the 3rd edition if you do get Billo, it has extensive revisions. Billo does more than stats-- it also shows how Excel is used in labs for reactions, computations, etc. Must have for any chem library.Library Picks reviews only for the benefit of Amazon shoppers and has nothing to do with Amazon, the authors, manufacturers or publishers of the items we review. We always buy the items we review for the sake of objectivity, and although we search for gems, are not shy about trashing an item if it's a waste of time or money for Amazon shoppers. If the reviewer identifies herself, her job or her field, it is only as a point of reference to help you gauge the background and any biases.
The book gave good examples about some misunderstood statistics terms and formulas. I used the often as a reference book; especially when I need a quick refresher for a project at work. I wished I had this book in graduated school!
Great small reference book to keep around to quickly remind you what certain statistical tests are used for what purpose.
good quality
Good book
Great introductory book for statistical analysis tools used by chemists.
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