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

...

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 ...

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 ...

266 pages 84 Tables black & white; 90 Illustrations black & white Urdan Timothy C (Santa Clara University USA) ...

How do you choose the appropriate statistical method for any given research task? What are the features that discern one statistical method from another & for which research projects are they appropriate to use? Written specifically with the undergraduate psychology student in mind & for those who desire an explanation for the use of statistics in psychological research without the mathematics this refreshing & much-needed introduction is invaluable for any psychology students who don't get numbers' Breaking away from the traditional numerical approaches Jones delivers an engaging & insightful read into the rationale behind the use of statistics drawing upon non-numerical examples & scenarios from both psychological literature & everyday life to explain key statistical concepts Learn about the methods for testing populations & samples standard errors inferential & descriptive statistics as well as variables & participants This is an ideal companion to core textbooks & will serve a clearer understanding of statistical methods in psychology By reading this book students can hope to gain a better sense of what makes empirically valid research & learn to critically evaluate facts & figure in any presented research The foundations of psychology's claims are the empiricism of well-conducted & reliable data ...