The statistical programming

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  • This book is about data analysis and the programming language called R. This is rapidly becoming the de facto standard among professionals, and is used in every conceivable discipline from science and medicine to business and engineering. R is more than just a computer program; it is a statistical programming environment and language. R is free and open source and is therefore available to everyone with a computer. It is very powerful and flexible, but it is also unlike most of the computer programs you are likely used to.

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  • The U.S. National Science Foundation (NSF) has long collected information on the number and characteristics of individuals with education or employment in science and engineering and related fields in the United States. One of the three vehicles employed by NSF for collecting this information is the National Survey of College Graduates (NSCG).

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  • An early definition of mathematics in terms of logic was Benjamin Peirce's "the science that draws necessary conclusions" (1870).[24] In the Principia Mathematica, Bertrand Russell and Alfred North Whitehead advanced the philosophical program known as logicism, and attempted to prove that all mathematical concepts, statements, and principles can be defined and proven entirely in terms of symbolic logic. A logicist definition of mathematics is Russell's "All Mathematics is Symbolic Logic" (1903)

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  • In this paper, we describe a Dynamic Programming (DP) based search algorithm for statistical translation and present experimental results. The statistical translation uses two sources of information: a translation model and a language model. The language model used is a standard bigram model. For the translation lnodel, the alignment probabilities are made dependent on the differences in the alignment positions rather than on the absolute positions.

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  • Stochastic unification-based grammars (SUBGs) define exponential distributions over the parses generated by a unificationbased grammar (UBG). Existing algorithms for parsing and estimation require the enumeration of all of the parses of a string in order to determine the most likely one, or in order to calculate the statistics needed to estimate a grammar from a training corpus.

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  • INTENDED FOR CLASS USE OR SELF-STUDY, this text aspires to introduce statistical methodology to a wide audience, simply and intuitively, through resampling from the data at hand. The resampling methods—permutations and the bootstrap—are easy to learn and easy to apply. They require no mathematics beyond introductory high-school algebra, yet are applicable in an exceptionally broad range of subject areas.

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  • Despite the gradual shift towards a market economy that commenced in 1986, and in spite of the emphasis on state owned enterprise (SOE) reform and privatization in the structural adjustment programs formulated since the mid-1990s, the state sector continues to play a leading role in the Vietnamese economy. The dominant position of the state sector is confirmed in official statistics and a variety of studies on the Vietnamese economy.

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  • This book is intended for a rigorous introductory Ph.D. level course in econometrics, or for use in a field course in econometric theory. It is based on lecture notes that I have developed during the period 1997-2003 for the first semester econometrics course “Introduction to Econometrics” in the core of the Ph.D. program in economics at the Pennsylvania State University. Initially these lecture notes were written as a companion to Gallant’s (1997) textbook, but have been developed gradually into an alternative textbook.

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  • Combines a cookbook approach with the use of PCs and programmable calculators. Contains statistics suitable for the low number of samples, high-pressure situations commonly found in established analytical methods with algorithms to eliminate statistical table handling, sample programs and data sets th

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  • Essentials of Statistics for the Social and Behavioral Sciences distills the overwhelming amount of material covered in introductory statistics courses into a handy, practical resource for students and professionals. This accessible guide covers basic to advanced concepts in a clear, concrete, and readable style. Essentials of Statistics for the Social and Behavioral Sciences guides you to a better understanding of basic concepts of statistical methods. Numerous practical tips are presented for selecting appropriate statistical procedures.

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  • The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.

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  • Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.

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  • A complete practical tutorial for RStudio, designed keeping in mind the needs of analysts and R developers alike. Step-by-step examples that apply the principles of reproducible research and good programming practices to R projects. Learn to effectively generate reports, create graphics, and perform analysis, and even build R-packages with RStudio.

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  • We introduce a novel search algorithm for statistical machine translation based on dynamic programming (DP). During the search process two statistical knowledge sources are combined: a translation model and a bigram language model. This search algorithm expands hypotheses along the positions of the target string while guaranteeing progressive coverage of the words in the source string. We present experimental results on the Verbmobil task.

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  • This volume describes the essential tools and techniques of statistical signal processing. At every stage, theoretical ideas are linked to specific applications in communications and signal processing. The book begins with an overview of basic probability, random objects, expectation, and second-order moment theory, followed by a wide variety of examples of the most popular random process models and their basic uses and properties.

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  • The application hitcounter presents a simple hitcounter for your website. It is possible to enter blocklists in a configfile so robots and perhaps your own computer are excluded from the statistics. There are still a lot of improvements possible ofcourse like setting a cookie so you get only one hit per sessio

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  • This is the first of two reports that address the complex issue of incorporating the needs of climate research into the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NPOESS, which has been driven by the imperative of reliably providing short-term weather information, is itself a union of heretofore separate civilian and military programs. It is a marriage of convenience to eliminate needless duplication and reduce cost, one that appears to be working.

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  • Before starting with the process of acquiring, correcting and measuring images, it seems important to spend a chapter addressing the important question of just what it is that can and should be measured, and what cannot or should not be. The temptation to just measure everything that software can report, and hope that a good statistics program can extract some meaningful parameters, is both naïve and dangerous. No statistics program can correct, for instance, for the unknown but potentially large bias that results from an inappropriate sampling procedure.

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  • I am grateful for the contributions that many people have made to this book. Ed Maggin was the first to teach me Statistical Thermodynam-ics and his class notes were always a point of reference. The late Ted H. Davis gave me encouragement and invaluable feedback. Dan Bolin-tineanu and Thomas Jikku read the final draft and helped me make many corrections. Many thanks go to the students who attended my course in Statistical Thermodynamics and who provided me with many valuable comments regarding the structure of the book.

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  • Learn to program a computer without the jargon and complexity of many programming books. Suitable for anybody age 10 to 100+ who wants to learn and is ready to experiment. This book engages through media (sound, color, shapes, and text to speech) and then introduces the concepts of structured programming (loops, conditions, variables...), using BASIC-256. You will learn to program as you make animations, games, and fun applications. Full source code to example programs are given to start experimentation and self exploration....

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