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Data Analysis with Excel®: An Introduction for Physical Scientists, by Les Kirkup
Download Data Analysis with Excel®: An Introduction for Physical Scientists, by Les Kirkup
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Data analysis is of central importance in the education of scientists. This book offers a compact and readable introduction to techniques relevant to physical science students. The material is thoroughly integrated with the popular and powerful spreadsheet package Excel by Microsoft. Excel features of most relevance to the analysis of experimental data in the physical sciences are dealt with in some detail. Fully worked problems reinforce basic principles. Underlying assumptions and range of applicability of techniques are discussed, though detailed derivations of basic equations are mostly avoided or confined to the appendices.
- Sales Rank: #2499011 in Books
- Brand: Brand: Cambridge University Press
- Published on: 2002-03-18
- Original language: English
- Number of items: 1
- Dimensions: 9.72" h x 1.10" w x 6.85" l, 1.64 pounds
- Binding: Paperback
- 468 pages
- Used Book in Good Condition
Review
"Overall I found the book excellent..." The Physicist
"Kirkup provides a very readable way for readers to learn basic principles of data analysis for the physical sciences and incoporates spreadsheets as flexible and powerful utilities...This excellent resource blends the power and utility of a popular spreadsheet package with relevant data analysis techniques and successfully combines content, relevance, and access to contemporary data analysis tools." Choice
About the Author
Les Kirkup is Associate Professor in the School of Physics and Advanced Materials, University of Technology, Sydney. A dedicated lecturer, many of his educational developments have focused on enhancing the laboratory experience of undergraduate students. In May 2011, he was awarded an Australian Learning and Teaching Council National Teaching Fellowship.
Most helpful customer reviews
0 of 0 people found the following review helpful.
An Excellent Reference Book
By Michael Harcrow
This is quite a large book with loads of information in it. If you use excel for anything beyond simple adding and subtracting, you will find useful advice in here. Well worth the price.
21 of 21 people found the following review helpful.
A disappointing book
By A second reader
This is an introductory book on Excel for physical scientists. Cambridge University Press deserves a compliment for a beautifully produced volume. Unfortunately, its contents are disappointing, because the text contains serious errors and omissions. The most obvious error is the statement, on page 308, that Excel does not provide built in facilities for fitting equations to data using nonlinear least squares. Excel does provide these, in the form of Solver, but the reader will look in vain for any mention of Solver in this book. (Figure 9.1 on page 365 shows that the author indeed has not bothered to activate the Solver Add-in.) The most serious omission is that the existence of user-definable functions and macros is not mentioned either. This leaves out two of the most powerful features of Excel: nonlinear least squares, and user programmability.
Another major problem with this book is that it doesn't show the reader how to use the spreadsheet effectively, but often goes out of its way to make easy things difficult. The almost exclusive emphasis in this book is on least squares methods, yet these are handled quite clumsily. On page 244, e.g., the linear correlation coefficient is computed from its formula by calculating the necessary sums, rather than by taking advantage of the fact that Linest, Regression, and Trendline all provide this parameter or its square. On page 284 the reader is shown the matrix algebra for fitting data to a parabola, and then told that "The built in matrix functions of Excel are well suited to estimating parameters in linear least squares problems", as if Linest, Regression, and Trendline are not there to take care of such tedious data manipulations. Likewise, on page 290, the user is not informed that Linest and Regression can also do multivariate analysis, but instead is instructed to do this the hard way, again by setting up and solving matrix equations. It is as if the author hasn't quite figured out yet that the spreadsheet has several built-in facilities specifically designed to make such least squares problems user-friendly.
In comparison with other books vying for the scientific spreadsheet market it is difficult to come up with any area in which Kirkup's book has the edge over its competitors: Billo (2nd ed., Wiley, 2001), Bloch (2nd ed., Wiley, 2003), de Levie (Oxford, 2004), Gottfried (2nd ed., McGraw-Hill, 2002), Liengme (3rd ed., Newnes, 2002), and Orvis (2nd ed., Sybex, 1996) all provide much more useful information, and don't make their readers jump through unnecessary hoops either.
1 of 4 people found the following review helpful.
A must for engineering statistics
By A Customer
If you are doing an engineering statistics course this book is of a hell of a lot more value than Engineering Statistics by Hubele, Montgomery and Runger.
This book teaches you how to do statistics using excel.
Should be aplicable for most statistics but is of great
assistance if your doing Engineering statistics and get stuck without much support.
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