Data analysis for physical scientists featuring Excel

The ability to summarise data, compare models and apply computer-based analysis tools are vital skills necessary for studying and working in the physical sciences. This textbook supports undergraduate students as they develop and enhance these skills. Introducing data analysis techniques, this textb...

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Bibliographic Details
Main Author: Kirkup, Les
Format: eBook
Language:English
Published: Cambridge Cambridge University Press 2011
Edition:Second edition
Subjects:
Online Access:
Collection: Cambridge Books Online - Collection details see MPG.ReNa
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100 1 |a Kirkup, Les 
130 0 |a Data analysis with Excel 
245 0 0 |a Data analysis for physical scientists  |b featuring Excel  |c Les Kirkup 
250 |a Second edition 
260 |a Cambridge  |b Cambridge University Press  |c 2011 
300 |a xv, 510 pages  |b digital 
505 0 |a Machine generated contents note: 1. Introduction to scientific data analysis; 2. Excel and data analysis; 3. Data distributions I; 4. Data distributions II; 5. Measurement, error and uncertainty; 6. Least squares I; 7. Least squares II; 8. Non-linear least squares; 9. Tests of significance; 10. Data analysis tools in Excel and the Analysis ToolPak; Appendixes; Answers to exercises and end-of-chapter problems; References; Index 
653 |a Research / Statistical methods / Data processing 
653 |a Electronic spreadsheets 
653 |a Microsoft Excel (Computer file) 
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520 |a The ability to summarise data, compare models and apply computer-based analysis tools are vital skills necessary for studying and working in the physical sciences. This textbook supports undergraduate students as they develop and enhance these skills. Introducing data analysis techniques, this textbook pays particular attention to the internationally recognised guidelines for calculating and expressing measurement uncertainty. This new edition has been revised to incorporate Excel® 2010. It also provides a practical approach to fitting models to data using non-linear least squares, a powerful technique which can be applied to many types of model. Worked examples using actual experimental data help students understand how the calculations apply to real situations. Over 200 in-text exercises and end-of-chapter problems give students the opportunity to use the techniques themselves and gain confidence in applying them. Answers to the exercises and problems are given at the end of the book