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Schaum's Outline of Theory and Problems of Probability (2nd Edition)
Schaum's Outline of Theory and Problems of Probability (2nd Edition)

Schaum's Outline of Probability, Second Edition, focuses on non-calculus probability theory, making it ideal for humanities and science majors who study practical statistics for problem solving. This popular Schaum's study guide provides new material on descriptive statistics, hi-square distribution, and more.

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Python for Data Science For Dummies (For Dummies (Computer/Tech))
Python for Data Science For Dummies (For Dummies (Computer/Tech))

Unleash the power of Python for your data analysis projectswith For Dummies!

Python is the preferred programming language for data scientistsand combines the best features of Matlab, Mathematica, and R intolibraries specific to data analysis and visualization. Pythonfor Data Science For Dummies shows you how to...

Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics)
Bayesian Models for Categorical Data (Wiley Series in Probability and Statistics)

The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical...

The Mathematics of Derivatives Securities with Applications in MATLAB
The Mathematics of Derivatives Securities with Applications in MATLAB

Quantitative Finance is expanding rapidly. One of the aspects ofthe recent financial crisis is that, given the complexity offinancial products, the demand for people with high numeracy skillsis likely to grow and this means more recognition will be given toQuantitative Finance in existing and new course structuresworldwide. Evidence has...

The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Springer Texts in Statistics)
The Bayesian Choice: From Decision-Theoretic Foundations to Computational Implementation (Springer Texts in Statistics)

The main purpose of statistical theory is to derive from observations of a random phenomenon an inference about the probability distribution underlying this phenomenon. That is, it provides either an analysis (description) of a past phenomenon, or some predictions about a future phenomenon of a similar nature. In this book, we insist...

Introduction to Cryptography (Undergraduate Texts in Mathematics)
Introduction to Cryptography (Undergraduate Texts in Mathematics)

Cryptography is a key technology in electronic security systems. Modern cryptograpic techniques have many uses, such as to digitally sign documents, for access control, to implement electronic money, and for copyright protection. Because of these important uses it is necessary that users be able to estimate the efficiency and security...

Introduction to Probability with Statistical Applications
Introduction to Probability with Statistical Applications
This book provides a calculus-based introduction to probability and statistics. It contains enough material for two semesters but, with judicious selection, it can be used as a textbook for a one-semester course, either in probability and statistics or in probability alone.

Each section contains many examples and exercises and, in the
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Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)
Numerical Issues in Statistical Computing for the Social Scientist (Wiley Series in Probability and Statistics)
At last—a social scientist's guide through the pitfalls of modern statistical computing
Addressing the current deficiency in the literature on statistical methods as they apply to the social and behavioral sciences, Numerical Issues in Statistical Computing for the Social Scientist seeks to provide readers with a unique practical
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Fundamentals of Project Management (Worksmart Series)
Fundamentals of Project Management (Worksmart Series)
Although managing projects has been going on for thousands of years, the practice has only recently been
recognized as a discipline in its own right. Suddenly master’s-level degree programs are springing up at
schools throughout the world, and certificate programs are being offered as well. Not only that, but some
organizations
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Fuzzy Probabilities: New Approach and Applications (Studies in Fuzziness and Soft Computing)
Fuzzy Probabilities: New Approach and Applications (Studies in Fuzziness and Soft Computing)
In probability and statistics we often have to estimate probabilities and parameters in probability distributions using a random sample. Instead of using a point estimate calculated from the data we propose using fuzzy numbers which are constructed from a set of confidence intervals. In probability calculations we apply constrained fuzzy arithmetic...
Statistics and Probability for Engineering Applications, First Edition
Statistics and Probability for Engineering Applications, First Edition
More than ever, American industry especially the semiconductor industry is using statistical methods to improve its competitive edge in the world market. It is becoming more imperative that graduate engineers have solid statistical know-how, yet engineers in industry typically are not well-prepared to use statistics and they are fuzzy about how to...
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms
Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms
Estimation of Distribution Algorithms (EDAs) are a set of algorithms in the Evolutionary Computation (EC) field characterized by the use of explicit probability distributions in optimization. Contrarily to other EC techniques such as the broadly known Genetic Algorithms (GAs) in EDAs, the crossover and mutation operators are substituted by the...
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