Muutke küpsiste eelistusi

E-raamat: Bayesian Methods in Statistics: From Concepts to Practice

  • Formaat: 272 pages
  • Ilmumisaeg: 10-Nov-2021
  • Kirjastus: Sage Publications Ltd
  • Keel: eng
  • ISBN-13: 9781529769319
  • Formaat - PDF+DRM
  • Hind: 49,39 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Formaat: 272 pages
  • Ilmumisaeg: 10-Nov-2021
  • Kirjastus: Sage Publications Ltd
  • Keel: eng
  • ISBN-13: 9781529769319

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This book gets you up and running with doing complex Bayesian statistics, focussing on applied analysis rather than maths.

This book walks you through learning probability and statistics from a Bayesian point of view. 

From an introduction to probability theory through to frameworks for doing rigorous calculations of probability, it discusses Bayes’ Theorem before illustrating how to use it in a variety of different situations with data addressing social and psychological issues.

The book also:

  • Equips you with coding skills in the statistical modelling language Stan and programming language R.
  • Discusses how Bayesian approaches to statistics compare to classical approaches.
  • Introduces Markov Chain Monte Carlo methods for doing Bayesian statistics through computer simulations, so you understand how Bayesian solutions are implemented.

Features include an introduction to each chapter and a chapter summary to help you check your learning. All the examples and data used in the book are also available in the online resources so you can practice at your own pace.

For readers with some understanding of basic mathematical functions and notation, this book will get you up and running so you can do Bayesian statistics with confidence.

Arvustused

A concise and engaging introduction to Bayesian statistics for newcomers in the social sciences, using real world data to highlight these powerful methods of statistical inference. -- Alex Jones

Chapter 1: Probability
Chapter 2: Probability distributions
Chapter 3: Models and inference
Chapter 4: Relationships between variables
Chapter 5: General models
Chapter 6: Questionnaires and non-quantitative responses
Chapter 7: Multiple issues
Mel Slater is a Distinguished Investigator at the University of Barcelona, and co-Director of the Event Lab (Experimental Virtual Environments for Neuroscience and Technology). He was previously Professor of Virtual Environments at University College London (UCL) in the Department of Computer Science. He was awarded the 2005 IEEE Virtual Reality Career Award: In Recognition of Pioneering Achievements in Theory and Applications of Virtual Reality.

He is Field Editor of Frontiers in Virtual Reality, and Chief Editor of the Human Behaviour in VR section. He was awarded the Humboldt Research Prize from Germany in 2020. He is a Fellow of the Royal Statistical Society.