Chiudi

Aggiungi l'articolo in

Chiudi
Aggiunto

L’articolo è stato aggiunto alla lista dei desideri

Chiudi

Crea nuova lista

Probability and Statistical Inference: From Basic Principles to Advanced Models - Miltiadis C. Mavrakakis,Jeremy Penzer - cover
Probability and Statistical Inference: From Basic Principles to Advanced Models - Miltiadis C. Mavrakakis,Jeremy Penzer - cover
Dati e Statistiche
Wishlist Salvato in 0 liste dei desideri
Probability and Statistical Inference: From Basic Principles to Advanced Models
Disponibile in 5 giorni lavorativi
53,43 €
-5% 56,24 €
53,43 € 56,24 € -5%
Disp. in 5 gg lavorativi
Chiudi
Altri venditori
Prezzo e spese di spedizione
ibs
53,43 € Spedizione gratuita
disponibile in 5 giorni lavorativi disponibile in 5 giorni lavorativi
Info
Nuovo
Altri venditori
Prezzo e spese di spedizione
ibs
53,43 € Spedizione gratuita
disponibile in 5 giorni lavorativi disponibile in 5 giorni lavorativi
Info
Nuovo
Altri venditori
Prezzo e spese di spedizione
Chiudi

Tutti i formati ed edizioni

Chiudi
Probability and Statistical Inference: From Basic Principles to Advanced Models - Miltiadis C. Mavrakakis,Jeremy Penzer - cover
Chiudi

Promo attive (0)

Descrizione


Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without sacrificing mathematical rigour, bridging the gap between the many excellent introductory books and the more advanced, graduate-level texts. The book introduces and explores techniques that are relevant to modern practitioners, while being respectful to the history of statistical inference. It seeks to provide a thorough grounding in both the theory and application of statistics, with even the more abstract parts placed in the context of a practical setting. Features: •Complete introduction to mathematical probability, random variables, and distribution theory. •Concise but broad account of statistical modelling, covering topics such as generalised linear models, survival analysis, time series, and random processes. •Extensive discussion of the key concepts in classical statistics (point estimation, interval estimation, hypothesis testing) and the main techniques in likelihood-based inference. •Detailed introduction to Bayesian statistics and associated topics. •Practical illustration of some of the main computational methods used in modern statistical inference (simulation, boostrap, MCMC). This book is for students who have already completed a first course in probability and statistics, and now wish to deepen and broaden their understanding of the subject. It can serve as a foundation for advanced undergraduate or postgraduate courses. Our aim is to challenge and excite the more mathematically able students, while providing explanations of statistical concepts that are more detailed and approachable than those in advanced texts. This book is also useful for data scientists, researchers, and other applied practitioners who want to understand the theory behind the statistical methods used in their fields.
Leggi di più Leggi di meno

Dettagli

Chapman & Hall/CRC Texts in Statistical Science
2022
Paperback / softback
444 p.
Testo in English
234 x 156 mm
453 gr.
9780367749125
Chiudi
Aggiunto

L'articolo è stato aggiunto al carrello

Chiudi

Aggiungi l'articolo in

Chiudi
Aggiunto

L’articolo è stato aggiunto alla lista dei desideri

Chiudi

Crea nuova lista

Chiudi

Chiudi

Siamo spiacenti si è verificato un errore imprevisto, la preghiamo di riprovare.

Chiudi

Verrai avvisato via email sulle novità di Nome Autore