Data modeling for the sciences: applications, basics, computations
With the increasing prevalence of big data and sparse data, and rapidly growing data-centric approaches to scientific research, students must develop effective data analysis skills at an early stage of their academic careers. This detailed guide to data modeling in the sciences is ideal for students...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2023
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| Schlagworte: | |
| Online-Zugang: | DE-12 DE-634 DE-92 DE-29 Volltext |
| Zusammenfassung: | With the increasing prevalence of big data and sparse data, and rapidly growing data-centric approaches to scientific research, students must develop effective data analysis skills at an early stage of their academic careers. This detailed guide to data modeling in the sciences is ideal for students and researchers keen to develop their understanding of probabilistic data modeling beyond the basics of p-values and fitting residuals |
| Beschreibung: | Also issued in print: 2023. - Includes bibliographical references and index |
| Beschreibung: | 1 Online-Ressource (xv, 415 Seiten) Illustrationen |
| ISBN: | 9781009089555 |
| DOI: | 10.1017/9781009089555 |
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| doi_str_mv | 10.1017/9781009089555 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
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| institution | BVB |
| isbn | 9781009089555 |
| language | English |
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| spelling | Pressé, Steve (DE-588)1306481929 aut Data modeling for the sciences applications, basics, computations Steve Pressé, Ioannis Sgouralis Cambridge Cambridge University Press 2023 1 Online-Ressource (xv, 415 Seiten) Illustrationen txt rdacontent sti rdacontent c rdamedia cr rdacarrier Also issued in print: 2023. - Includes bibliographical references and index With the increasing prevalence of big data and sparse data, and rapidly growing data-centric approaches to scientific research, students must develop effective data analysis skills at an early stage of their academic careers. This detailed guide to data modeling in the sciences is ideal for students and researchers keen to develop their understanding of probabilistic data modeling beyond the basics of p-values and fitting residuals Research / Statistical methods Science / Statistical methods Probabilities Mathematical statistics Sgouralis, Ioannis (DE-588)1306483522 aut Erscheint auch als Druck-Ausgabe 978-1-009-09850-2 https://doi.org/10.1017/9781009089555 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Pressé, Steve Sgouralis, Ioannis Data modeling for the sciences applications, basics, computations Research / Statistical methods Science / Statistical methods Probabilities Mathematical statistics |
| title | Data modeling for the sciences applications, basics, computations |
| title_auth | Data modeling for the sciences applications, basics, computations |
| title_exact_search | Data modeling for the sciences applications, basics, computations |
| title_exact_search_txtP | Data modeling for the sciences applications, basics, computations |
| title_full | Data modeling for the sciences applications, basics, computations Steve Pressé, Ioannis Sgouralis |
| title_fullStr | Data modeling for the sciences applications, basics, computations Steve Pressé, Ioannis Sgouralis |
| title_full_unstemmed | Data modeling for the sciences applications, basics, computations Steve Pressé, Ioannis Sgouralis |
| title_short | Data modeling for the sciences |
| title_sort | data modeling for the sciences applications basics computations |
| title_sub | applications, basics, computations |
| topic | Research / Statistical methods Science / Statistical methods Probabilities Mathematical statistics |
| topic_facet | Research / Statistical methods Science / Statistical methods Probabilities Mathematical statistics |
| url | https://doi.org/10.1017/9781009089555 |
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