1.

Record Nr.

UNINA9910774729003321

Autore

Mathai Arak M.

Titolo

Probability and Statistics : A Course for Physicists and Engineers / / Arak M. Mathai, Hans J. Haubold

Pubbl/distr/stampa

Berlin ; ; Boston : , : De Gruyter, , [2017]

©2018

Descrizione fisica

1 online resource (604 p.)

Collana

De Gruyter Textbook

Classificazione

SK 800

Disciplina

519.2

Soggetti

Engineering - Statistical methods

Probabilities

Modellbildung

Statistik

Versuchsplanung

Wahrscheinlichkeitsrechnung

Wahrscheinlichkeitstheorie

MATHEMATICS / Probability & Statistics / General

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Frontmatter -- Introduction / Mathai, A. M. / Haubold, Hans J. -- Preface / Mathai, A. M. / Haubold, Hans J. -- Acknowledgement -- Contents -- List of Tables -- List of Symbols -- 1. Random phenomena -- 2. Probability -- 3. Random variables -- 4. Expected values -- 5. Commonly used discrete distributions -- 6. Commonly used density functions -- 7. Joint distributions -- 8. Some multivariate distributions -- 9. Collection of random variables -- 10. Sampling distributions -- 11. Estimation -- 12. Interval estimation -- 13. Tests of statistical hypotheses -- 14. Model building and regression -- 15. Design of experiments and analysis of variance -- 16. Questions and answers -- Tables of percentage points -- References -- Index

Sommario/riassunto

This book offers an introduction to concepts of probability theory, probability distributions relevant in the applied sciences, as well as basics of sampling distributions, estimation and hypothesis testing. As



a companion for classes for engineers and scientists, the book also covers applied topics such as model building and experiment design. ContentsRandom phenomenaProbabilityRandom variablesExpected valuesCommonly used discrete distributionsCommonly used density functionsJoint distributionsSome multivariate distributionsCollection of random variablesSampling distributionsEstimationInterval estimationTests of statistical hypothesesModel building and regressionDesign of experiments and analysis of varianceQuestions and answers