Designing algorithms to recommend items such as news articles & movies to users is a challenging task in numerous web applications The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives Major technical challenges are high dimensional prediction with sparse data & constructing high dimensional sequential designs to collect data for user modeling & system design This comprehensive treatment of the statistical issues that arise in recommender systems

Includes:: detailed in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods) bilinear random-effects models (matrix factorization) & scalable model fitting using modern computing paradigms like Map Reduce The authors draw upon their vast experience working with such large-scale systems at Yahoo! & Linked In & bridge the gap between theory & practice by illustrating complex concepts with examples from applications they are directly involved with

...

Statistical methods in modern research increasingly entail developing estimating & testing models for data Rather than rigid methods of data analysis the need today is for more flexible methods for modelling data In this logical easy-to-follow & exceptionally clear book David Flora provides a comprehensive survey of the major statistical procedures currently used His innovative model-based approach teaches you how to Understand & choose the right statistical model to fit your data Match substantive theory & statistical models Apply statistical procedures hands-on with example data analyses Develop & use graphs to understand data & fit models to data Work with statistical modeling principles using any software package Learn by applying with input & output files for R SAS SPSS & Mplus Statistical Methods for the Social & Behavioural Sciences A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics & begin using the right statistical modeling method for their own data It is particularly suited to second or advanced courses in statistical methods across the social & behavioural sciences ...

This book provides a general introduction to the ideas & methods of statistical mechanics with the principal aim of meeting the needs of Master's students in chemical mechanical & materials science engineering Extensive introductory information is presented on many general physics topics in which students in engineering are inadequately trained ranging from the Hamiltonian formulation of classical mechanics to basic quantum mechanics electromagnetic fields in matter intermolecular forces & transport phenomena Since engineers should be able to apply physical concepts the book also focuses on the practical applications of statistical physics to material science & to cutting-edge technologies with brief but informative sections on for example interfacial properties disperse systems nucleation magnetic materials superfluidity & ultralow temperature technologies The book adopts a graded approach to learning the opening four basic-level chapters being followed by advanced "starred" sections in which special topics are discussed Its relatively informal style including the use of musical metaphors to guide the reader through the text will aid self-learning ...

Statistical Rethinking A Bayesian Course with Examples in R & Stan builds readers' knowledge of & confidence in statistical modeling Reflecting the need for even minor programming in today's model-based statistics the book pushes readers to perform step-by-step calculations that are usually automated This unique computational approach ensures that readers understand enough of the details to make reasonable choices & interpretations in their own modeling work The text presents generalized linear multilevel models from a Bayesian perspective relying on a simple logical interpretation of Bayesian probability & maximum entropy It covers from the basics of regression to multilevel models The author also discusses measurement error missing data & Gaussian process models for spatial & network autocorrelation By using complete R code examples throughout this book provides a practical foundation for performing statistical inference Designed for both Ph D students & seasoned professionals in the natural & social sciences it prepares them for more advanced or specialized statistical modeling Web Resource The book is accompanied by an R package (rethinking) that is available on the author's website & Git Hub The two core functions (map & map 2stan) of this package allow a variety of statistical models to be constructed from standard model formulas ...

Fully endorsed by OCR & revised to match the 2005

Specification this series has been carefully revised by experienced

...

The new edition of this bestseller continues to demystify the world of statistics for health care professionals Revised throughout the 11th Edition features new material in the areas of binary data to deal with relative risk absolute risk & the evidence-based criteria of numbers needed to treat 192 pages Campbell Michael J ...

Statistics For Dummies 2nd Edition (9781119293521) was previously published as Statistics For Dummies 2nd Edition (9780470911082) While this version features a new Dummies cover & design the content is the same as the prior release & should not be considered a new or updated product The fun & easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear practical explanations of statistical ideas techniques formulas & calculations with lots of examples that show you how these concepts apply to your everyday life Statistics For Dummies shows you how to interpret & critique graphs & charts determine the odds with probability guesstimate with complete confidence using confidence intervals set up & carry out a hypothesis test compute statistical formulas & more Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods & classroom protocol Packed with practical advice & real-world problems Statistics For Dummies gives you everything you need to analyze & interpret data for enhanced classroom or on-the-job performance ...

This book was written for those who need to know how to collect analyze & present data It is meant to be a first course for practitioners a book for private study or brush-up on statistics & supplementary reading for general statistics classes The book is untraditional both with respect to the choice of topics & the presentation Topics were determined by what is most useful for practical statistical work & the presentation is as non-mathematical as possible The book contains many examples using statistical functions in spreadsheets In this second edition new topics have been included eg within the area of statistical quality control in order to make the book even more useful for practitioners working in industry ...

Statistics for the Health Sciences is a highly readable & accessible textbook on understanding statistics for the health sciences both conceptually & via the SPSS programme The authors give clear explanations of the concepts underlying statistical analyses & descriptions of how these analyses are applied in health science research without complex maths formulae The textbook takes students from the basics of research design hypothesis testing & descriptive statistical techniques through to more advanced inferential statistical tests that health science students are likely to encounter The strengths & weaknesses of different techniques are critically appraised throughout & the authors emphasise how they may be used both in research & to inform best practice care in health settings Exercises & tips throughout the book allow students to practice using SPSS The companion website provides further practical experience of conducting statistical analyses Features include multiple choice questions for both student & lecturer use full Powerpoint slides for lecturers practical exercises using SPSS additional practical exercises using SAS & RThis is an essential textbook for students studying beginner & intermediate level statistics across the health sciences ...

This mainstream accessible textbook provides an introduction to statistics using the General Linear Model a method that shows the interconnectedness of statistical concepts The textbook is intended for undergraduate social science majors in a one-semester statistics course ...