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 and 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 and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation.By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling.Web ResourceThe book is accompanied by an R package (rethinking) that is available on the author's website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

    The book's approach interweaves traditional topics with data analysis and reflects the use of the computer with close ties to the practice of statistics. The author stresses analysis of data, examines real problems with real data, and motivates the theory. The book's descriptive statistics, graphical displays, and realistic applications stand in strong contrast to traditional texts which are set in abstract settings.

    Never fear, I have a hunchThere is a match for every bunch!"Greg Tang, a lifelong lover of math, shares the techniques that have helped him solve problems in the most creative ways! Harry Briggs's vibrant & inviting illustrations create a perfect environment for these innovative games. So open your mind-and have fun!"This...clever math book uses rhyming couplets... riddles...visual clues to help the reader find new ways to group numbers for quick counting...A winning addition!" --Kirkus

    The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.

    More than 500 solved Examples to make concepter very clear. Exhautive Exercises for Each topic.

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    It uses examples and exercise sets, with clear explanations of problem-solving techniqes and material on the further theory of functions.

     This top-selling, theorem-proof text presents a careful treatment of the principal topics of linear algebra, and illustrates the power of the subject through a variety of applications. It emphasizes the symbiotic relationship between linear transformations and matrices, but states theorems in the more general infinite-dimensional case where appropriate.

    Ian Hacking here presents a philosophical critique of early ideas about probability, induction and statistical inference and the growth of this new family of ideas in the fifteenth, sixteenth and seventeenth centuries. The contemporary debate centres round such figures as Pascal, Leibniz and Jacques Bernoulli. What brought about the change in ideas? The author invokes in his explanation a wider intellectual framework involving the growth of science, economics and the theology of the period.

    Premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps readers discover the nature of statistics and understand its essential role in scientific research.

    Reuben Hersh argues the contrary, that mathematics must be understood as a human activity, a social phenomenon, part of human culture, historically evolved, and intelligible only in a social context. Hersh pulls the screen back to reveal mathematics as seen by professionals, debunking many mathematical myths, and demonstrating how the humanist idea of the nature of mathematics more closely resembles how mathematicians actually work. At the heart of his book is a fascinating historical account of the mainstream of philosophy--ranging from Pythagoras, Descartes, and Spinoza, to Bertrand Russell, David Hilbert, and Rudolph Carnap--followed by the mavericks who saw mathematics as a human artifact, including Aristotle, Locke, Hume, Mill, and Lakatos.What is Mathematics, Really? reflects an insider's view of mathematical life, and will be hotly debated by anyone with an interest in mathematics or the philosophy of science.

     KPOP BTS QUIZ BOOK covers various quiz questions about each member of the group, as well as many interesting facts as a group, such as... "On the November 22, BTS was announced to be officially recognized by THIS organization as a musical group with the most Twitter engagement." "On the very first Episode of American Hustle Life, BTS travels to THIS CITY to learn Hip Hop." "THIS member was an underground rapper in Daegu." "J-Hope said that the kind of super power he would like to have is...?" "When Jimin was asked to describe and compare Rap Monster to something other than a human, he said Rap Monster is like..." "When V celebrated his Birthday (2013.12.30 at MBC Gayo Daejun), he shared birthday with THIS famous singer. He said to V “Hey, is it your Birthday today? It’s mine too! Let’s blow the candle together.” "True or False...? Jungkook's dream when he was little is to become a badminton player, but changed his mind after listening to..." Can you answer the questions? If you can't, that's totally fine cause that's the best way of getting to know your favorite BTS oppa's!

    Linear algebra is tightly integrated into the text.

    The R language is recognised as one of the most powerful and flexible statistical software packages, and it enables the user to apply many statistical techniques that would be impossible without such software to help implement such large data sets.

    Other new features include a chapter on simulation, a section on Gibbs sampling, what you should know boxes at the end of each chapter, and remarks to highlight difficult concepts.