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Advanced Excel for Scientific Data Analysis
Combining an easy-going style with an emphasis on practical applications, this greatly expanded second edition is remarkable in scope and coverage. As reviews of the first edition noted, the term "advanced" in the title is not used lightly. Less than a third of its 700+ pages are devoted to
least squares analysis, yet the reader will learn about many aspects of this ubiquitous method that are seldom found together in one multivariate and polynomial centering, the statistical uncertainty in uncertainty estimates, how to use the covariance, singular value decomposition, the pros
and cons of weighted least squares, moving equidistant least squares, nonlinear least squares, and imprecision contours.
There are lucid chapters on Fourier transformation, convolution and deconvolution, and digital simulation of ordinary differential equations. A new chapter is devoted to some common but often only crudely used mathematical methods, such as numerical differentiation, Romberg integration, and cubic
spline interpolation. Another new chapter shows how to use linear algebra on the spreadsheet with Volpi's extensive matrix toolbox of custom functions and macros. A third, newly added chapter describes how to set up the spreadsheet to make it less error-prone, and how to get superaccurate answers in
Excel. The substantially enlarged chapter on writing functions and macros now has a set of MacroMorsels to illustrate specific points that otherwise might trip up novice programmers, and a detailed description of Excel's extensive debugging tools. All this is presented in an easily digestible
format, illustrated with many examples from the literature, and supported by a large collection of open-access (i.e., fully transparent and user-modifiable) custom functions and macros.
least squares analysis, yet the reader will learn about many aspects of this ubiquitous method that are seldom found together in one multivariate and polynomial centering, the statistical uncertainty in uncertainty estimates, how to use the covariance, singular value decomposition, the pros
and cons of weighted least squares, moving equidistant least squares, nonlinear least squares, and imprecision contours.
There are lucid chapters on Fourier transformation, convolution and deconvolution, and digital simulation of ordinary differential equations. A new chapter is devoted to some common but often only crudely used mathematical methods, such as numerical differentiation, Romberg integration, and cubic
spline interpolation. Another new chapter shows how to use linear algebra on the spreadsheet with Volpi's extensive matrix toolbox of custom functions and macros. A third, newly added chapter describes how to set up the spreadsheet to make it less error-prone, and how to get superaccurate answers in
Excel. The substantially enlarged chapter on writing functions and macros now has a set of MacroMorsels to illustrate specific points that otherwise might trip up novice programmers, and a detailed description of Excel's extensive debugging tools. All this is presented in an easily digestible
format, illustrated with many examples from the literature, and supported by a large collection of open-access (i.e., fully transparent and user-modifiable) custom functions and macros.
667 pages, Paperback
First published August 1, 2003
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Displaying 1 of 1 review
February 28, 2015
One of the best. Its all in there.
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