692 rezultatov
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Sample Size Calculations in Clinical Research(2020) CHOW, SHEIN-CHUNG (DUKE UNIV, USA),SHAO, JUN (DEPARTMENT OF STATISTICS, UNIVERSITY OF WISCONSIN, USA),WANG, HANSHENG,LOKHNYGINA, YULIYA (DUKE UNIVERSITY SCHOOL OF MEDICINE, DURHAM, NC, USA)Like the well-regarded and bestselling second edition, Sample Size Calculations in Clinical Research, Third Edition, presents statistical procedures for performing sample size calculations during various phases of clinical research and development. This nVezava: Mehka78,08 € -
Statistical Rethinking(2020) MCELREATH, RICHARD (MAX PLANCK INSTITUTE FOR EVOLUTIONARY ANTHROPOLOGY, LEIPZIG, GERMANY)Statistical Rethinking: A Bayesian Course with Examples in R and Stan, Second Edition builds knowledge/confidence in statistical modeling. Pushes readers to perform step-by-step calculations (usually automated.) Unique, computational approach.Vezava: Trda132,94 € -
Probabilistic Numerics(2022) HENNIG, PHILIPP (EBERHARD-KARLS-UNIVERSITAT TUBINGEN, GERMANY),OSBORNE, MICHAEL A. (UNIVERSITY OF OXFORD),KERSTING, HANS P. (ECOLE NORMALE SUPERIEURE, PARIS)This text provides a first comprehensive introduction to probabilistic numerics, aimed at Masters' and PhD students, as well as postgraduate researchers in artificial intelligence, computer science, statistics, and applied mathematics. It contains extensiVezava: Trda99,75 € -
Introduction to Modern Analysis(2022) KANTOROVITZ, SHMUEL (PROFESSOR EMERITUS OF MATHEMATICS, PROFESSOR EMERITUS OF MATHEMATICS, BAR-ILAN UNIVERSITY),VISELTER, AMI (SENIOR LECTURER, SENIOR LECTURER, UNIVERSITY OF HAIFA)Aimed at advanced undergraduate and graduate students this textbook provides an introduction to the vast and crucial area of modern analysis. This new edition begins by covering the theoretical bases, gradually moving on to more advanced subjects and pracVezava: Mehka99,75 € -
Mathematics for Machine Learning(2020) DEISENROTH, MARC PETER (UNIVERSITY COLLEGE LONDON),FAISAL, A. ALDO (IMPERIAL COLLEGE LONDON),ONG, CHENG SOONThis self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculusVezava: Mehka76,02 € -
Data-Driven Science and Engineering(2022) BRUNTON, STEVEN L. (UNIVERSITY OF WASHINGTON),KUTZ, J. NATHAN (UNIVERSITY OF WASHINGTON)Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB®, new chapters on reinVezava: Trda91,00 € -
Introduction to Probability and Statistics for Engineers and Scientists(2021) ROSS, SHELDON M. (PROFESSOR, DEPARTMENT OF INDUSTRIAL AND SYSTEMS ENGINEERING, UNIVERSITY OF SOUTHERN CALIFORNIA, LOS ANGELES, USA)Vezava: Trda154,90 € -
First Course in Machine Learning(2020) ROGERS, SIMON (UNIVERSITY OF GLASGOW, UNITED KINGDOM),GIROLAMI, MARK (UNIVERSITY COLLEGE LONDON, UNITED KINGDOM)The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, ClaVezava: Mehka75,24 € -
How Charts Lie(2020) CAIRO, ALBERTO (UNIVERSITY OF MIAMI)A leading data visualisation expert explores the negative—and positive-influences that charts have on our perception of truthVezava: Mehka21,61 € -
Sabermetrics(2022) COSTA, GABRIEL B. (VISITING PROFESSOR, DEPARTMENT OF MATHEMATICAL SCIENCES, UNITED STATES MILITARY ACADEMY, WEST POINT, NY, USA)Vezava: Mehka134,78 € -
Getting Started with R(2017) BECKERMAN, ANDREW P. (DEPARTMENT OF ANIMAL AND PLANT SCIENCE, UNIVERSITY OF SHEFFIELD),CHILDS, DYLAN Z. (DEPARTMENT OF ANIMAL AND PLANT SCIENCE, UNIVERSITY OF SHEFFIELD),PETCHEY, OWEN L. (DEPARTMENT OF EVOLUTIONARY BIOLOGY AND ENVIRONMENTAL STUDIES, UNIVERSITY OF ZURICH)A popular entry-level guide into the use of R as a statistical programming and data management language for students, post-docs, and seasoned researchers now in a new revised edition, incorporating the updates in the R environment, and also adding guidancVezava: Mehka79,60 € -
Measurement(2016) HAND, DAVID J. (SENIOR RESEARCH INVESTIGATOR AND EMERITUS PROFESSOR OF MATHEMATICS AT IMPERIAL COLLEGE, LONDON, AND CHIEF SCIENTIFIC ADVISOR TO WINTON CAPITAL MANAGEMENT)This Very Short Introduction explores the concept of measurement, its mathematical underpinnings, and its wide range of application from the sciences and social sciences to economics and commerce.Vezava: Mehka14,01 € -
Time Series for Data Science(2022) WOODWARD, WAYNE A. (SOUTHERN METHODIST UNIVERSITY, DALLAS, TEXAS, USA),SADLER, BIVIN PHILIP (TECHNICAL ASSISTANT PROFESSOR, SOUTHERN METHODIST UNIVERSITY),ROBERTSON, STEPHENPractical Time Series Analysis for Data Science is an accessible guide that doesn’t require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed.Vezava: Trda186,45 € -
Model-Based Clustering and Classification for Data Science(2019) BOUVEYRON, CHARLES,CELEUX, GILLES,MURPHY, T. BRENDAN (UNIVERSITY COLLEGE DUBLIN),RAFTERY, ADRIAN E. (UNIVERSITY OF WASHINGTON)This accessible but rigorous introduction is written for advanced undergraduates and beginning graduate students in data science, as well as researchers and practitioners. It shows how a statistical framework yields sound estimation, testing and predictioVezava: Trda127,75 € -
High-Dimensional Probability(2018) VERSHYNIN, ROMAN (UNIVERSITY OF CALIFORNIA, IRVINE)The data sciences are moving fast, and probabilistic methods are both the foundation and a driver. This highly motivated text brings beginners up to speed quickly and provides working data scientists with powerful new tools. Ideal for a basic second coursVezava: Trda99,75 € -
Brownian Motion, Martingales, and Stochastic Calculus(2016) LE GALL, JEAN-FRANCOISThis book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales.Vezava: Trda62,07 € -
Course in Mathematical Statistics and Large Sample Theory(2016) BHATTACHARYA, RABI,LIN, LIZHEN,PATRANGENARU, VICTORThis graduate-level textbook is primarily aimed at graduate students of statistics, mathematics, science, and engineering who have had an undergraduate course in statistics, an upper division course in analysis, and some acquaintance with measure theoretiVezava: Trda170,23 € -
Statistical(2020) REUBEN, ANTHONYAn accessible guide to interrogating the many statistics we are bombarded by every day.Vezava: Mehka12,61 €
