The Chemical Educator, Vol. 7, No. 2, S1430-4171(02)02549-4, 10.1007/s00897020549a, © 2002 Springer-Verlag New York, Inc.
How to Use Excel in Analytical Chemistry and in General Scientific Data Analysis. By Robert de Levie. Cambridge University Press, U.K. xiv + 483 pp. US$44.95. ISBN 0-521-64484-4.
Roy W. Clark, Middle Tennessee State University, Murfreesboro, TN, firstname.lastname@example.org
Any book about the use of spreadsheets to enhance the data analysis in any field of study is likely to be prejudged as a collection of spreadsheet templates. The hope is that these templates can be copied and used by instructors and students for assignments. This book is not a collection of such templates. It is a smoothly written, excellent tutorial about how such spreadsheets are created, and thus how you can create your own quite complex spreadsheets. By complex spreadsheets I mean those that utilize Excel’s Solver and Visual Basic abilities for applications (VBA) that do much more than simpler spreadsheets do.
As the title implies, the examples chosen are of interest to analytical chemists, but any chemist whose interest includes the manipulation of data according to some mathematical theory can profit from a study of de Levie’s methods. Analytical chemists will find more than the usual Gaussian plots and titration curves. There are spectrophotometric spreadsheets, chromatography simulations, peak-area calculations, and even polarography and other voltammetry experiments. By the way, the titration curves use the “progress of titration” method. This follows the procedure of plotting the ratio of the volumes involved versus the pH, instead of trying to expressing pH as a function of titrant volume. This approach yields multiparameter equations that can be fit to the titration data by nonlinear-regression techniques. The equivalence point can then be deduced from the fit rather than from some point of inflection. This book would be worth its cost if it contained nothing but this section on titrations.
The chapter on kinetics is not a tutorial on how to plot and fit data to integrated rate equations. It is instead a tutorial on how to approach kinetics by numerical simulation of the differential equations involved. This approach, in the limit of small step size, of course yields the same integrated equations, but by starting from the differential equations, it allows an extension of the spreadsheet capabilities to heterogeneous catalysis and to oscillating reactions.
The final chapter on spreadsheet programming includes, among other useful VBA macros, a bidirectional Fourier-transform macro. This is advanced spreadsheeting in its most elegant form.
Finally, I offer my impression of de Levie’s writing style. It is clear, as brief as is possible, and gives an underlying perspective on what these spreadsheets are doing that I consider refreshingly honest. For example, when discussing Solver’s ability, or lack of it, to find the correct minima, I quote
Note that these limitations make eminent sense once you understand what Solver does, and are no different from those encountered when we extract information from ordinary experiments, without a computer. It is just that we often come to expect too much of programs or of machines. Have you ever seen a horse win a race without a jockey? Solver is like that: a very competent program that could be a champ—but only when you tell it where to go, and how to get there.
Although the book does not include a CD-ROM containing the spreadsheets, the VBA macros are available both on a Web site and in the text. Sorry, no templates, but a very good book. No analytical chemistry teacher, no serious analytical chemistry student, should fail to acquire this book.