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1. 

Probability, Statistics and Random Processes

Probability, Statistics and Random Processes

By: Pappu Kousalya

Publisher: Pearson India

Publication Date: 28-FEB-2013

Insert Date: 30-JUL-2014

Slots: 1.0

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Probability, Statistics and Random Processes is designed to meet the requirements of students and is intended for beginners to help them understand the concepts from the first principles. Spread across 16 chapters, it discusses the theoretical aspects that have been refined and updated to reflect the current developments in the subjects. It expounds on theoretical concepts that have immense practical applications, giving adequate proofs to establish significant theorems. ...

2. 

Statistics in Education and Psychology

Statistics in Education and Psychology

By: R. P. Pathak

Publisher: Pearson India

Publication Date: 23-APR-2011

Insert Date: 30-JUL-2014

Slots: 1.0

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Statistics in Education and Psychology aims to develop a coherent, logical and comprehensive outlook towards statistics. The subject involves a wide range of observations, measurements, tools, techniques and data analysis. This book covers diverse topics like measures of central tendency, measures of variability, the correlation method, normal probability curve (NPC), significance of difference of means, analysis of variance, non-parametric chi-square, standard score and T-score. ...

3. 

Fundamentals of Applied Probability and Random Processes, 2nd Edition

Fundamentals of Applied Probability and Random Processes, 2nd Edition

By: Oliver Ibe

Publisher: Academic Press

Publication Date: 13-JUN-2014

Insert Date: 27-JUL-2014

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The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their...

4. 

Bayesian Probability Theory

Bayesian Probability Theory

By: Wolfgang von der Linden; Volker Dose; Udo von Toussaint

Publisher: Cambridge University Press

Publication Date: 31-MAY-2014

Insert Date: 25-JUL-2014

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From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for...

5. 

Better Business Decisions from Data

Better Business Decisions from Data

By: Peter Kenny

Publisher: Apress

Publication Date: 30-JUN-2014

Insert Date: 15-JUL-2014

Slots: 1.0

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"Everyone encounters statistics on a daily basis. They are used in proposals, reports, requests, and advertisements, among others, to support assertions, opinions, and theories. Unless you're a trained statistician, it can be bewildering. What are the numbers really saying or not saying? Better Business Decisions from Data: Statistical Analysis for Professional Success provides the answers to these questions and more. It will show you how to use statistical data to improve small, every-day management judgments as well as major business decisions with potentially serious consequences.Author...

6. 

Using R for Statistics

Using R for Statistics

By: Sarah Stowell

Publisher: Apress

Publication Date: 29-JUN-2014

Insert Date: 04-JUL-2014

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" R is a popular and growing open source statistical analysis and graphics environment as well as a programming language and platform. If you need to use a variety of statistics, then Using R for Statistics will get you the answers to most of the problems you are likely to encounter.Using R for Statistics is a problem-solution primer for using R to set up your data, pose your problems and get answers using a wide array of statistical tests. The book walks you through R basics and how to use R to accomplish a wide variety statistical operations. You'll be able to navigate the R system,...

7. 

Regression Analysis by Example, 4th Edition

Regression Analysis by Example, 4th Edition

By: Samprit Chatterjee; Ali S. Hadi

Publisher: Wiley-Interscience

Publication Date: 21-JUL-2006

Insert Date: 01-JUL-2014

Slots: 1.0

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The essentials of regression analysis through practical applications Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgement. Regression Analysis by Example, Fourth Edition has been expanded and thoroughly updated to reflect recent advances in the field. The emphasis continues to be on exploratory data analysis rather than statistical theory. The book offers in-depth treatment of regression...

8. 

Haskell Data Analysis Cookbook

Haskell Data Analysis Cookbook

By: Nishant Shukla

Publisher: Packt Publishing

Publication Date: 25-JUN-2014

Insert Date: 27-JUN-2014

Slots: 1.0

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Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes A practical and concise guide to using Haskell when getting to grips with data analysis Recipes for every stage of data analysis, from collection to visualization In-depth examples demonstrating various tools, solutions and techniques In Detail This book will take you on a voyage through all the steps involved in data analysis. It provides synergy between Haskell and data modeling, consisting of carefully chosen examples featuring some of the most popular...

9. 

Probabilistic Approaches to Recommendations

Probabilistic Approaches to Recommendations

By: Nicola Barbieri; Giuseppe Manco; Ettore Ritacco

Publisher: Morgan & Claypool Publishers

Publication Date: 01-MAY-2014

Insert Date: 06-JUN-2014

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The importance of accurate recommender systems has been widely recognized by academia and industry, and recommendation is rapidly becoming one of the most successful applications of data mining and machine learning. Understanding and predicting the choices and preferences of users is a challenging task: real-world scenarios involve users behaving in complex situations, where prior beliefs, specific tendencies, and reciprocal influences jointly contribute to determining the preferences of users toward huge amounts of information, services, and products. Probabilistic modeling represents a...

10. 

Data Scientist: The Definitive Guide to Becoming a Data Scientist

Data Scientist: The Definitive Guide to Becoming a Data Scientist

By: Zacharias Voulgaris, PhD

Publisher: Technics Publications

Publication Date: 09-MAY-2014

Insert Date: 13-MAY-2014

Slots: 1.0

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As our society transforms into a data-driven one, the role of the Data Scientist is becoming more and more important. If you want to be on the leading edge of what is sure to become a major profession in the not-too-distant future, this book can show you how.  Each chapter is filled with practical information that will help you reap the fruits of big data and become a successful Data Scientist: Learn what big data is and how it differs from traditional data through its main characteristics: volume, variety, velocity, and veracity. Explore the different types of Data Scientists and...

11. 

Nonparametric Statistics: A Step-by-Step Approach, 2nd Edition

Nonparametric Statistics: A Step-by-Step Approach, 2nd Edition

By: 

Publisher: John Wiley & Sons

Publication Date: 19-MAY-2014

Insert Date: 01-MAY-2014

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"...a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." -CHOICE This Second Edition presents a practical and understandable approach that enhances and expands the statistical toolset for readers. This book includes: New coverage of the sign test and the Kolmogorov-Smirnov two-sample test in an effort to offer a logical and natural progression to statistical power SPSS (Version 21) software and...

12. 

A First Course in Machine Learning

A First Course in Machine Learning

By: Simon Rogers; Mark Girolami

Publisher: Chapman and Hall/CRC

Publication Date: 25-OCT-2011

Insert Date: 18-APR-2014

Slots: 1.0

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Requiring minimal mathematical prerequisites, this classroom-tested text covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms, including classification, clustering, and projection algorithms. The MATLAB<SUP>®</SUP>/Octave scripts available online enable readers to recreate plots that appear in the book and investigate changing model specifications and parameter values. By experimenting with the various algorithms and concepts, readers see how an abstract set of equations can be used to solve real problems. A...

13. 

Multi-Label Dimensionality Reduction

Multi-Label Dimensionality Reduction

By: Liang Sun; Shuiwang Ji; Jieping Ye

Publisher: Chapman and Hall/CRC

Publication Date: 04-NOV-2013

Insert Date: 18-APR-2014

Slots: 1.0

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The data mining and machine learning literature currently lacks a unified treatment of multi-label dimensionality reduction that incorporates both algorithmic developments and applications. Addressing this shortfall, this book covers the methodological developments, theoretical properties, computational aspects, and applications of many multi-label dimensionality reduction algorithms, including existing dimensionality reduction algorithms and new developments of traditional algorithms. It illustrates how to apply the algorithms to solve real-world problems. A supplementary website provides...

14. 

Examples and Problems in Mathematical Statistics

Examples and Problems in Mathematical Statistics

By: 

Publisher: John Wiley & Sons

Publication Date: 24-FEB-2014

Insert Date: 08-APR-2014

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Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important...

15. 

Nonparametric Statistical Methods, 3rd Edition

Nonparametric Statistical Methods, 3rd Edition

By: 

Publisher: John Wiley & Sons

Publication Date: 25-NOV-2013

Insert Date: 22-MAR-2014

Slots: 1.0

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Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."—Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any...

16. 

Introduction to Stochastic Models

Introduction to Stochastic Models

By: Marius Iosifescu; Nikolaos Limnios; Gheorghe Oprisan

Publisher: John Wiley & Sons

Publication Date: 19-APR-2010

Insert Date: 11-MAR-2014

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This book provides a pedagogical examination of the way in which stochastic models are encountered in applied sciences and techniques such as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their particular cases: Poisson, renewal processes, branching processes, Ehrenfest models, genetic models, optimal stopping, reliability, reservoir theory, storage models, and queuing systems. Given this comprehensive treatment of the subject, students and researchers in applied sciences, as well as anyone looking for an...

17. 

Explorations in Topology

Explorations in Topology, Second Edition

By: David Gay

Publisher: Elsevier

Publication Date: 04-DEC-2013

Insert Date: 28-FEB-2014

Slots: 1.0

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Explorations in Topology, Second Edition, provides students a rich experience with low-dimensional topology (map coloring, surfaces, and knots), enhances their geometrical and topological intuition, empowers them with new approaches to solving problems, and provides them with experiences that will help them make sense of future, more formal topology courses. The book's innovative story-line style models the problem-solving process, presents the development of concepts in a natural way, and engages students in meaningful encounters with the material. The updated end-of-chapter...

18. 

Foundational and Applied Statistics for Biologists Using R

Foundational and Applied Statistics for Biologists Using R

By: Ken Aho

Publisher: Chapman and Hall/CRC

Publication Date: 13-DEC-2013

Insert Date: 26-FEB-2014

Slots: 1.0

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Full of biological applications, exercises, and interactive graphical examples, this text presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. R code and other materials are available online. ...

19. 

Analysis of Multivariate and High-Dimensional Data

Analysis of Multivariate and High-Dimensional Data

By: Inge Koch

Publisher: Cambridge University Press

Publication Date: 30-NOV-2013

Insert Date: 25-FEB-2014

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Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical...

20. 

An Introduction to Kalman Filtering with MATLAB Examples

An Introduction to Kalman Filtering with MATLAB Examples

By: Narayan Kovvali; Mahesh Banavar; Andreas Spanias

Publisher: Morgan & Claypool Publishers

Publication Date: 01-SEP-2013

Insert Date: 19-FEB-2014

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The Kalman filter is the Bayesian optimum solution to the problem of sequentially estimating the states of a dynamical system in which the state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a variety of applications, e.g., target tracking, guidance and navigation, and communications systems. The purpose of this book is to present a brief introduction to Kalman filtering. The theoretical framework of the Kalman filter is first presented, followed by examples showing its use in practical applications....