Probability and Statistics by Example PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Probability and Statistics by Example PDF full book. Access full book title Probability and Statistics by Example by Yuri Suhov. Download full books in PDF and EPUB format.
Author: Yuri Suhov
Publisher: Cambridge University Press
ISBN: 1107603587
Category : Mathematics
Languages : en
Pages : 477
Get Book
Book Description
A valuable resource for students and teachers alike, this second edition contains more than 200 worked examples and exam questions.
Author: Yuri Suhov
Publisher: Cambridge University Press
ISBN: 1107603587
Category : Mathematics
Languages : en
Pages : 477
Get Book
Book Description
A valuable resource for students and teachers alike, this second edition contains more than 200 worked examples and exam questions.
Author: Yuri Suhov
Publisher: Cambridge University Press
ISBN: 1316062201
Category : Mathematics
Languages : en
Pages :
Get Book
Book Description
Probability and statistics are as much about intuition and problem solving as they are about theorem proving. Consequently, students can find it very difficult to make a successful transition from lectures to examinations to practice because the problems involved can vary so much in nature. Since the subject is critical in so many applications from insurance to telecommunications to bioinformatics, the authors have collected more than 200 worked examples and examination questions with complete solutions to help students develop a deep understanding of the subject rather than a superficial knowledge of sophisticated theories. With amusing stories and historical asides sprinkled throughout, this enjoyable book will leave students better equipped to solve problems in practice and under exam conditions.
Author: F.M. Dekking
Publisher: Springer Science & Business Media
ISBN: 1846281687
Category : Mathematics
Languages : en
Pages : 488
Get Book
Book Description
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books
Author: Dr. J. S. Chitode
Publisher: Technical Publications
ISBN: 9333223924
Category : Education
Languages : en
Pages : 268
Get Book
Book Description
First chapter deals with probability and random variable discussion. CDF, PDF and two dimensional random variables are discussed. Second chapter presents various useful probability distribution models. It also presents useful statistical averages such as mean, moments, variance, etc. Third chapter presents basic statistics concepts. Mean, median, mode, moments, variance, Kurtosis, skewness are discussed. Correlation, regression, Chebyshev inequality are also presented. Fourth chapter discusses formation of hypothesis, tests of significance and chi-square distribution. Last chapter presents curve fitting using straight line and second degree parabola.
Author: Michael J. Evans
Publisher: Macmillan
ISBN: 9780716747420
Category : Mathematics
Languages : en
Pages : 704
Get Book
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: T. T. Soong
Publisher: John Wiley & Sons
ISBN: 0470868155
Category : Mathematics
Languages : en
Pages : 406
Get Book
Book Description
This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.
Author: Norman Matloff
Publisher: CRC Press
ISBN: 0429687117
Category : Business & Economics
Languages : en
Pages : 295
Get Book
Book Description
Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.
Author: Richard von Mises
Publisher: Academic Press
ISBN: 1483264025
Category : Mathematics
Languages : en
Pages : 708
Get Book
Book Description
Mathematical Theory of Probability and Statistics focuses on the contributions and influence of Richard von Mises on the processes, methodologies, and approaches involved in the mathematical theory of probability and statistics. The publication first elaborates on fundamentals, general label space, and basic properties of distributions. Discussions focus on Gaussian distribution, Poisson distribution, mean value variance and other moments, non-countable label space, basic assumptions, operations, and distribution function. The text then ponders on examples of combined operations and summation of chance variables characteristic function. The book takes a look at the asymptotic distribution of the sum of chance variables and probability inference. Topics include inference from a finite number of observations, law of large numbers, asymptotic distributions, limit distribution of the sum of independent discrete random variables, probability of the sum of rare events, and probability density. The text also focuses on the introduction to the theory of statistical functions and multivariate statistics. The publication is a dependable source of information for researchers interested in the mathematical theory of probability and statistics
Author: Walter A. Rosenkrantz
Publisher: CRC Press
ISBN: 158488813X
Category : Mathematics
Languages : en
Pages : 680
Get Book
Book Description
Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create
Author: Michael Baron
Publisher: CRC Press
ISBN: 1498760600
Category : Mathematics
Languages : en
Pages : 475
Get Book
Book Description
Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make o
