Statistical methods for data analysis: with applications in particle physics (Record no. 1165)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02018 a2200217 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250416174048.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240426b2023|||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9783031199332 |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 539.72 L57, 3 |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Lista, Luca |
| Relator term | Author |
| 245 ## - TITLE STATEMENT | |
| Title | Statistical methods for data analysis: with applications in particle physics |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 3rd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | Springer, |
| Year of publication | 2023. |
| Place of publication | Switzerland: |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xxx, 334p.; 23cms. |
| 500 ## - GENERAL NOTE | |
| General note | This third edition expands on the original material. Large portions of the text have been reviewed and clarified. More emphasis is devoted to machine learning including more modern concepts and examples. This book provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP).<br/><br/>It starts with an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. Following, the author discusses Monte Carlo methods with emphasis on techniques like Markov Chain Monte Carlo, and the combination of measurements, introducing the best linear unbiased estimator. More advanced concepts and applications are gradually presented, including unfolding and regularization procedures, culminating in the chapter devoted to discoveries and upper limits.<br/><br/>The reader learns through many applications in HEP where the hypothesis testing plays a major role and calculations of look-elsewhere effect are also presented. Many worked-out examples help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Statistical methods |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Data analysis and Machine learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Hypothesis testing |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Permanent Location | Current Location | Shelving location | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|---|---|---|---|
| Dr. S. R. Ranganathan Library | Dr. S. R. Ranganathan Library | General Stacks | 539.72 L57,3 | 3185 | Books |