A student's guide to data and error analysis:
All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its ina...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2011
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UBM01 URL des Erstveröffentlichers |
| Zusammenfassung: | All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xii, 225 pages) |
| ISBN: | 9780511921247 |
| DOI: | 10.1017/CBO9780511921247 |
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| 245 | 1 | 0 | |a A student's guide to data and error analysis |c Herman J.C. Berendsen |
| 246 | 1 | 3 | |a A Student's Guide to Data & Error Analysis |
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| 505 | 8 | |a Part I. Data and Error Analysis: 1. Introduction; 2. The presentation of physical quantities with their inaccuracies; 3. Errors: classification and propagation; 4. Probability distributions; 5. Processing of experimental data; 6. Graphical handling of data with errors; 7. Fitting functions to data; 8. Back to Bayes: knowledge as a probability distribution; Answers to exercises -- Part II. Appendices: A1. Combining uncertainties; A2. Systematic deviations due to random errors; A3. Characteristic function; A4. From binomial to normal distributions; A5. Central limit theorem; A6. Estimation of the varience; A7. Standard deviation of the mean; A8. Weight factors when variances are not equal; A11. Least squares fitting -- Part III. Python codes -- Part IV. Scientific data | |
| 520 | |a All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference | ||
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Datensatz im Suchindex
| _version_ | 1804176887852826624 |
|---|---|
| any_adam_object | |
| author | Berendsen, Herman J. C. |
| author_facet | Berendsen, Herman J. C. |
| author_role | aut |
| author_sort | Berendsen, Herman J. C. |
| author_variant | h j c b hjc hjcb |
| building | Verbundindex |
| bvnumber | BV043943721 |
| classification_rvk | SK 910 UX 1100 |
| collection | ZDB-20-CBO |
| contents | Part I. Data and Error Analysis: 1. Introduction; 2. The presentation of physical quantities with their inaccuracies; 3. Errors: classification and propagation; 4. Probability distributions; 5. Processing of experimental data; 6. Graphical handling of data with errors; 7. Fitting functions to data; 8. Back to Bayes: knowledge as a probability distribution; Answers to exercises -- Part II. Appendices: A1. Combining uncertainties; A2. Systematic deviations due to random errors; A3. Characteristic function; A4. From binomial to normal distributions; A5. Central limit theorem; A6. Estimation of the varience; A7. Standard deviation of the mean; A8. Weight factors when variances are not equal; A11. Least squares fitting -- Part III. Python codes -- Part IV. Scientific data |
| ctrlnum | (ZDB-20-CBO)CR9780511921247 (OCoLC)757682711 (DE-599)BVBBV043943721 |
| dewey-full | 511/.43 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 511 - General principles of mathematics |
| dewey-raw | 511/.43 |
| dewey-search | 511/.43 |
| dewey-sort | 3511 243 |
| dewey-tens | 510 - Mathematics |
| discipline | Physik Mathematik |
| doi_str_mv | 10.1017/CBO9780511921247 |
| format | Electronic eBook |
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| isbn | 9780511921247 |
| language | English |
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| spelling | Berendsen, Herman J. C. Verfasser aut A student's guide to data and error analysis Herman J.C. Berendsen A Student's Guide to Data & Error Analysis Cambridge Cambridge University Press 2011 1 online resource (xii, 225 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Part I. Data and Error Analysis: 1. Introduction; 2. The presentation of physical quantities with their inaccuracies; 3. Errors: classification and propagation; 4. Probability distributions; 5. Processing of experimental data; 6. Graphical handling of data with errors; 7. Fitting functions to data; 8. Back to Bayes: knowledge as a probability distribution; Answers to exercises -- Part II. Appendices: A1. Combining uncertainties; A2. Systematic deviations due to random errors; A3. Characteristic function; A4. From binomial to normal distributions; A5. Central limit theorem; A6. Estimation of the varience; A7. Standard deviation of the mean; A8. Weight factors when variances are not equal; A11. Least squares fitting -- Part III. Python codes -- Part IV. Scientific data All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference Error analysis (Mathematics) Fehlerrechnung (DE-588)4153837-7 gnd rswk-swf Fehlerrechnung (DE-588)4153837-7 s 1\p DE-604 Erscheint auch als Druck-Ausgabe (DE-604)BV039132881 Erscheint auch als Druckausgabe 978-0-521-11940-5 Erscheint auch als Druckausgabe 978-0-521-13492-7 https://doi.org/10.1017/CBO9780511921247+ Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Berendsen, Herman J. C. A student's guide to data and error analysis Part I. Data and Error Analysis: 1. Introduction; 2. The presentation of physical quantities with their inaccuracies; 3. Errors: classification and propagation; 4. Probability distributions; 5. Processing of experimental data; 6. Graphical handling of data with errors; 7. Fitting functions to data; 8. Back to Bayes: knowledge as a probability distribution; Answers to exercises -- Part II. Appendices: A1. Combining uncertainties; A2. Systematic deviations due to random errors; A3. Characteristic function; A4. From binomial to normal distributions; A5. Central limit theorem; A6. Estimation of the varience; A7. Standard deviation of the mean; A8. Weight factors when variances are not equal; A11. Least squares fitting -- Part III. Python codes -- Part IV. Scientific data Error analysis (Mathematics) Fehlerrechnung (DE-588)4153837-7 gnd |
| subject_GND | (DE-588)4153837-7 |
| title | A student's guide to data and error analysis |
| title_alt | A Student's Guide to Data & Error Analysis |
| title_auth | A student's guide to data and error analysis |
| title_exact_search | A student's guide to data and error analysis |
| title_full | A student's guide to data and error analysis Herman J.C. Berendsen |
| title_fullStr | A student's guide to data and error analysis Herman J.C. Berendsen |
| title_full_unstemmed | A student's guide to data and error analysis Herman J.C. Berendsen |
| title_short | A student's guide to data and error analysis |
| title_sort | a student s guide to data and error analysis |
| topic | Error analysis (Mathematics) Fehlerrechnung (DE-588)4153837-7 gnd |
| topic_facet | Error analysis (Mathematics) Fehlerrechnung |
| url | https://doi.org/10.1017/CBO9780511921247+ |
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