Foundational research focuses on the theory, but theories are to be related also to other theories, experiments, facts in their domains, data, and to their uses in applications, whether of prediction, control, or explanation. A theory is to be identified through its class of models, but not so narrowly as to disallow these roles. The language of science is to be studied separately, with special reference to the relations listed above, and to the consequent need for resources other than for theoretical description. Peculiar to the foundational level are questions of completeness (specifically in the representation of measurement), and of interpretation (a topic beset with confusions of truth and evidence, and with inappropriate metalinguistic abstraction).

The Text Book Covers All Traditional As Well As Newly Emerging Topics In Statistical Methodology. A Broad General Description Of The Book Consists Of(I) A Lucid Presentation To The Motivation Of The Modern Axiomatic Approach To Probability.(Ii) Study Of All Major Distributions (Inclusive Of Circular, Log-Normal Singular) With New Interpretations Ofsome Distributions (Ex. Pareto, Logistic Etc.)(Iii) Model Oriented Approach To The Generations Of Normal, Log-Normal, Cauchy, Exponential, Gamma And Other Waiting Distributions And Their Characterizations.(Iv) Techniques Of Truncated And Censored Distributions Vis-À-Vis Parametric, Non-Parametric, Bayesian And Sequential Inference Procedures, The Backgrounds Of Which Have Been Provided.(V) Inclusion Of Classical Topics As Pearsonian Curves, Gram-Charlier Series And Orthogonal Polynomials.Some Of The Distinguishing Features Are As Follows: * Introducing The Concept Of Correlation As A Milestone In The Development Of Regression Theory. * A Large Number Of Solved Examples And A Wide Collection Of Unsolved Problems With Occasional Hints. * A Geometrical Treatment Of Non-Central X2.

This text provides a through, straightforward first course on basics statistics. Emphasizing the application of theory, it contains 200 fully worked examples and supplies exercises in each chapter-complete with hints and answers.

This book is intended for use in a rigorous introductory PhD level course in econometrics.

This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master’s students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills.

Get ready to create killer apps for iPad and iPhone on the new iOS 7! With Apple's introduction of iOS 7, demand for developers who know the new iOS will be high. You need in-depth information about the new characteristics and capabilities of iOS 7, and that's what you'll find in this book. If you have experience with C or C++, this guide will show you how to create amazing apps for iPhone, iPad, and iPod touch. You'll also learn to maximize your programs for mobile devices using iPhone SDK 7.0. Advanced topics such as security services, running on multiple iPlatforms, and local networking with Core Bluetooth are also covered. Prepares experienced developers to create great apps for the newest version of Apple's iOS Thoroughly covers the serious capabilities of iOS 7; information you need in order to make your apps stand out Delves into advanced topics including how to control multitasking, security services, running apps on multiple iPlatforms and iDevices, enabling in-app purchases, advanced text layout, and building a core foundation Also covers REST, advanced GCD, internationalization and localization, and local networking with Core Bluetooth iOS 7 Programming: Pushing the Limits will help you develop applications that take full advantage of everything iOS 7 has to offer.

Open the door to endless new app development possibilities Pushing the Limits with iOS 5 Programming is an expert guide for developers aiming to create unique applications for Apple's iPad 2, iPhone, and the iPod Touch, which includes the latest version of the Apple iPhone SDK, iOS 5. This text goes beyond the basics to keep you ahead of the technology curve and spark your innovative nature to create seamless, functional, and fun apps. With a focus on advanced techniques for app development, you will learn to differentiate your apps from all the rest. With this must-have book, you'll explore advanced coverage of a variety of development topics, such as developing with deep Objective-C, while you learn to create amazing applications for Apple's iPad 2, iPhone, and iPod touch. Veteran mobile developers and authors guide you through maximizing your programs as they delve into topics not commonly found elsewhere. Provides a solid foundation in the patterns of iOS Shares tips for running on multiple platforms and best using security services Discusses topics such as controlling multitasking, advanced text layout and more Demonstrates how to think differently with blocks and functional programming Teaches table view, performance, and money-making optimization Eliminates common challenges with memory management and iOS information flow Pushing the Limits with iOS 5 Programming allows you to take on the future with confidence in your new, stand-out app design skills.

This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly detection in financial markets, 3D virtual reality, monitoring of environmental data, convolutional neural networks, knowledge storage, data stream classification, and security in social networking. The respective papers highlight a wealth of issues in, and applications of, data science. Modern technologies allow us to store and transfer large amounts of data quickly. They can be very diverse - images, numbers, streaming, related to human behavior and physiological parameters, etc. Whether the data is just raw numbers, crude images, or will help solve current problems and predict future developments, depends on whether we can effectively process and analyze it. Data science is evolving rapidly. However, it is still a very young field. In particular, data science is concerned with visualizations, statistics, pattern recognition, neurocomputing, image analysis, machine learning, artificial intelligence, databases and data processing, data mining, big data analytics, and knowledge discovery in databases. It also has many interfaces with optimization, block chaining, cyber-social and cyber-physical systems, Internet of Things (IoT), social computing, high-performance computing, in-memory key-value stores, cloud computing, social computing, data feeds, overlay networks, cognitive computing, crowdsource analysis, log analysis, container-based virtualization, and lifetime value modeling. Again, all of these areas are highly interrelated. In addition, data science is now expanding to new fields of application: chemical engineering, biotechnology, building energy management, materials microscopy, geographic research, learning analytics, radiology, metal design, ecosystem homeostasis investigation, and many others.