Data analysis for physical scientists : featuring Excel - Kirkup, Les.; Kirkup, Les. (Cambridge : Cambridge University Press, 2011)
'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{u0CB0}10. 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'--
'Thorough analysis of experimental data frequently requires extensive numerical manipulation. Many tools exist to assist in the analysis of data, ranging from the pocket calculator to specialist computer based statistics packages. Despite limited editing and display options, the pocket calculator remains a well-used tool for basic analysis due to its low cost, convenience and reliability. Intensive data analysis may require a statistics package such as Systat or Origin . As well as standard functions, such as those used to determine means and standard deviations, these packages possess advanced features routinely required by researchers and professionals. Between the extremes of the pocket calculator and specialised statistics package is the spreadsheet. While originally designed for business users, spreadsheet packages are popular with other users due to their accessibility, versatility and ease of use. The inclusion of advanced features into spreadsheets means that, in many situations, a spreadsheet is a viable alternative to a statistics package'--
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.
Rev. ed. of: Data analysis with Excel. 2002.
Includes bibliographical references and index.
Keywords: Microsoft Excel (Computer file).; Research -- Statistical methods -- Data processing; Electronic spreadsheets