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Author: Francesca Biagini
Publisher: Springer
ISBN: 3319072544
Category : Mathematics
Languages : en
Pages : 246
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Book Description
This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.
Author: Francesca Biagini
Publisher: Springer
ISBN: 3319072544
Category : Mathematics
Languages : en
Pages : 246
Get Book
Book Description
This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.
Author: Boris Vladimirovich Gnedenko
Publisher: American Mathematical Soc.
ISBN: 9780821837467
Category : Computers
Languages : en
Pages : 540
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Book Description
Presents an introduction to probability and statistics. This book covers topics that include the axiomatic setup of probability theory, polynomial distribution, finite Markov chains, distribution functions and convolution, the laws of large numbers (weak and strong), characteristic functions, the central limit theorem, and Markov processes.
Author: Frank Louis Wolf
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 450
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Book Description
Author: Donald R. Byrkit
Publisher: Van Nostrand Reinhold Company
ISBN:
Category : Social sciences
Languages : en
Pages : 504
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Book Description
Organization and presentation of data; Measures of location and dispersion; Probability; Probability distributions; The binomial distribution; The normal distribution; Estimation of parameters; Hypothesis testing; The chi-square distribution; Analysis of variance; Correlation and regression; Nonparametric tests; Mathematical review.
Author: Rodger E. Ziemer
Publisher: Pearson
ISBN:
Category : Computers
Languages : en
Pages : 344
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Book Description
Responding to the needs of graduate engineers and ABET criteria, this volume illustrates the essentials of both probability and statistics through computer exercises. It features a wealth of computer exercises that provide experimental verification of probabilistic phenomena and a means for calculating and displaying complex results.
Author: Frank L. Wolf
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 450
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Book Description
Author: Harald Cramér
Publisher: Krieger Publishing Company
ISBN:
Category : Probabilities
Languages : en
Pages : 300
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Book Description
Author: Frank Louis Wolf
Publisher:
ISBN: 9781258768461
Category :
Languages : en
Pages : 338
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Book Description
Author: Michael J. Evans
Publisher: Macmillan
ISBN: 9780716747420
Category : Mathematics
Languages : en
Pages : 704
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Book Description
Unlike traditional introductory math/stat textbooks, Probability and Statistics: The Science of Uncertainty brings a modern flavor based on incorporating the computer to the course and an integrated approach to inference. From the start the book integrates simulations into its theoretical coverage, and emphasizes the use of computer-powered computation throughout.* Math and science majors with just one year of calculus can use this text and experience a refreshing blend of applications and theory that goes beyond merely mastering the technicalities. They'll get a thorough grounding in probability theory, and go beyond that to the theory of statistical inference and its applications. An integrated approach to inference is presented that includes the frequency approach as well as Bayesian methodology. Bayesian inference is developed as a logical extension of likelihood methods. A separate chapter is devoted to the important topic of model checking and this is applied in the context of the standard applied statistical techniques. Examples of data analyses using real-world data are presented throughout the text. A final chapter introduces a number of the most important stochastic process models using elementary methods. *Note: An appendix in the book contains Minitab code for more involved computations. The code can be used by students as templates for their own calculations. If a software package like Minitab is used with the course then no programming is required by the students.
Author: G. Jay Kerns
Publisher: Lulu.com
ISBN: 0557249791
Category : Education
Languages : en
Pages : 388
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Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
