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- 588 Seiten
- 21 Lesestunden
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R is now the most widely used statistical package/language in university statistics departments and many research organizations. Its great advantages are that for many years, it has been the leading statistical package/language and that it can be freely downloaded from the R website. This text provides a comprehensive treatment of the theory of statistical modelling in R with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions, making this book ideal for graduates and research students in applied statistics and a wide range of qualitative disciplines.
Buchkauf
Oxford Statistical Science Series - 35: Statistical Modelling in R, Murray A. Aitkin, Brian Francis, John Hinde, Ross Darnell
- Sprache
- Erscheinungsdatum
- 2009
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- Titel
- Oxford Statistical Science Series - 35: Statistical Modelling in R
- Sprache
- Englisch
- Autor*innen
- Murray A. Aitkin, Brian Francis, John Hinde, Ross Darnell
- Verlag
- Oxford University Press
- Erscheinungsdatum
- 2009
- Einband
- Paperback
- Seitenzahl
- 588
- ISBN10
- 0199219133
- ISBN13
- 9780199219131
- Reihe
- Schlagwörter
- Sozialwissenschaften, Historisches Thema, Computer & Internet, Kunst, Mathematik, Soziologie, Medizin, Forschung, Statistik, Datenverarbeitung, Epidemiologie
- Beschreibung
- R is now the most widely used statistical package/language in university statistics departments and many research organizations. Its great advantages are that for many years, it has been the leading statistical package/language and that it can be freely downloaded from the R website. This text provides a comprehensive treatment of the theory of statistical modelling in R with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions, making this book ideal for graduates and research students in applied statistics and a wide range of qualitative disciplines.