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.
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
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
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
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.
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.
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.
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.
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.
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.
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.
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....
Think Bayes is an introduction to Bayesian statistics using computational methods and Python programming language. Bayesian statistics are usually presented mathematically, but many of the ideas are easier to understand computationally. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
As part of its new Digital Government program, the National Science
Foundation (NSF) requested that the Computer Science and Telecommunications
Board (CSTB) undertake an in-depth study of how information
technology research and development could more effectively support
advances in the use of information technology in government.
Researchers in both machine Iranslation (e.g., Brown et al., 1990) and bilingual lexicography (e.g., Klavans and Tzoukermann, 1990) have recently become interested in studying parallel texts, texts such as the Canadian Hansards (parliamentary proceedings) which are available in multiple languages (French and English). This paper describes a method for aligning sentences in these parallel texts, based on a simple statistical model of character lengths. The method was developed and tested on a small trilingual sample of Swiss economic reports.
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.
In this work we present two extensions to the well-known dynamic programming beam search in phrase-based statistical machine translation (SMT), aiming at increased efﬁciency of decoding by minimizing the number of language model computations and hypothesis expansions.
We present the ﬁrst version of a new declarative programming language. Dyna has many uses but was designed especially for rapid development of new statistical NLP systems. A Dyna program is a small set of equations, resembling Prolog inference rules, that specify the abstract structure of a dynamic programming algorithm. It compiles into efﬁcient, portable, C++ classes that can be easily invoked from a larger application.
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.
Managers always want to do something to improve how their organizations
function. The combined effects of global competition, the growth in business
books and magazines, and business consultancy has led to a never-ending se-
ries of fads to fix organizations. It often seems that these do more to confuse
than inform people, leading to one change program after another, what the peo-
ple at Harley-Davidson dubbed many years ago, “AFP,” Another Fine Program
(often translated differently internally).