Data analysis for physical scientists : featuring Excel / Les Kirkup.

By:

Kirkup, Les

Contributor(s):

Kirkup, Les. Data analysis with Excel

Material type: Text

TextPublication details: Cambridge ; New York : Cambridge University Press, 2012.Edition: 2nd edDescription: 1 online resource (xv, 510 pages) : illustrationsContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781139160889
1139160885
9781139005258
1139005251
9781139158831
113915883X
1139157078
9781139157070
1139152475
9781139152471
1107226074
9781107226074
1280886730
9781280886737
1139159887
9781139159883
9786613728043
6613728047
1139155326
9781139155328

Subject(s): Genre/Form:

Additional physical formats: Print version:: Data analysis for physical scientists.DDC classification:

502.85/554 23

LOC classification:

Q180.55.S7 K57 2012eb

Other classification:

SCI040000

Online resources:

Click here to access online

Contents:

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.

Summary: "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"--Provided by publisherSummary: "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"--Provided by publisher

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Holdings
Item type	Home library	Collection	Call number	Materials specified	Status	Date due	Barcode
Electronic-Books	OPJGU Sonepat- Campus	E-Books EBSCO			Available

Revised edition of: Data analysis with Excel. 2002.

"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"--Provided by publisher

"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"--Provided by publisher