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Basic Statistics and Pharmaceutical Statistical Applications (Pharmacy Education Series)
by James E. De MuthBuilding on its best-selling predecessors, Basic Statistics and Pharmaceutical Statistical Applications, Third Edition covers statistical topics most relevant to those in the pharmaceutical industry and pharmacy practice. It focuses on the fundamentals required to understand descriptive and inferential statistics for problem solving. Incorporating
Basic Statistics for the Behavioral Sciences (Seventh Edition)
by Gary W. HeimanPacked with real-world illustrations and the latest data available, BASIC STATISTICS FOR THE BEHAVIORAL SCIENCES, 7e demystifies and fully explains statistics in a lively, reader-friendly format. The author's clear, patiently crafted explanations with an occasional touch of humor, teach readers not only how to compute an answer but also why they should perform the procedure or what their answer reveals about the data. Offering a conceptual-intuitive approach, this popular book presents statistics within an understandable research context, deals directly and positively with potential weaknesses in mathematics, and introduces new terms and concepts in an integrated way.
Basic Statistics in Criminology and Criminal Justice: Volume 1
by David Weisburd Chester Britt David B. Wilson Alese WooditchThis introductory textbook takes a building-block approach that emphasizes the application and interpretation of statistics in research in crime and justice. This text is meant for both students and professionals who want to gain a basic understanding of common statistical methods used in criminology and criminal justice before advancing to more complex statistical analyses in future volumes. This book emphasizes comprehension and interpretation. As the statistical methods discussed become more complex and demanding to compute, it integrates statistical software. It provides readers with an accessible understanding of popular statistical programs used to examine real-life crime and justice problems (including SPSS, Stata, and R). In addition, the book includes supplemental resources such as a glossary of key terms, practice questions, and sample data. Basic Statistics in Criminology and Criminal Justice aims to give students and researchers a core understanding of statistical concepts and methods that will leave them with the confidence and tools to tackle the statistical problems in their own research work.
Basic Stochastic Processes
by Raimondo Manca Jacques Janssen Pierre DevolderThis book presents basic stochastic processes, stochastic calculus including Lévy processes on one hand, and Markov and Semi Markov models on the other. From the financial point of view, essential concepts such as the Black and Scholes model, VaR indicators, actuarial evaluation, market values, fair pricing play a central role and will be presented. The authors also present basic concepts so that this series is relatively self-contained for the main audience formed by actuaries and particularly with ERM (enterprise risk management) certificates, insurance risk managers, students in Master in mathematics or economics and people involved in Solvency II for insurance companies and in Basel II and III for banks.
Basic Theory and Laboratory Experiments in Measurement and Instrumentation: A Practice-Oriented Guide (Lecture Notes in Electrical Engineering #663)
by Andrea Cataldo Nicola Giaquinto Antonio Masciullo Giuseppe Cannazza Ilaria Lorenzo Jacopo Nicolazzo Maria Teresa Meo Gianluca Parisi Federico Gaetani Egidio De Benedetto Alessando De MonteThis textbook offers a unique compendium of measurement procedures for experimental data acquisition. After introducing readers to the basic theory of uncertainty evaluation in measurements, it shows how to apply it in practice to conduct a range of laboratory experiments with instruments and procedures operating both in the time and frequency domains. Offering extensive practical information and hands-on tips on using oscilloscopes, spectrum analyzers and reflectometric instrumentation, the book shows readers how to deal with e.g. filter characterization, operational amplifiers, digital and analogic spectral analysis, and reflectometry-based measurements. For each experiment, it describes the corresponding uncertainty evaluation in detail. Bridging the gap between theory and practice, the book offers a unique, self-contained guide for engineering students and professionals alike. It also provides university teachers and professors with a valuable resource for their laboratory courses on electric and electronic measurements.
Basics of Bioinformatics: Lecture Notes of the Graduate Summer School on Bioinformatics of China
by Rui Jiang Xuegong Zhang Michael Q. ZhangThis book outlines 11 courses and 15 research topics in bioinformatics, based on curriculums and talks in a graduate summer school on bioinformatics that was held in Tsinghua University. The courses include: Basics for Bioinformatics, Basic Statistics for Bioinformatics, Topics in Computational Genomics, Statistical Methods in Bioinformatics, Algorithms in Computational Biology, Multivariate Statistical Methods in Bioinformatics Research, Association Analysis for Human Diseases: Methods and Examples, Data Mining and Knowledge Discovery Methods with Case Examples, Applied Bioinformatics Tools, Foundations for the Study of Structure and Function of Proteins, Computational Systems Biology Approaches for Deciphering Traditional Chinese Medicine, and Advanced Topics in Bioinformatics and Computational Biology. This book can serve as not only a primer for beginners in bioinformatics, but also a highly summarized yet systematic reference book for researchers in this field. Rui Jiang and Xuegong Zhang are both professors at the Department of Automation, Tsinghua University, China. Professor Michael Q. Zhang works at the Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
Basics of Continuum Plasticity
by Kwansoo Chung Myoung-Gyu LeeThis book describes the basic principles of plasticity for students and engineers who wish to perform plasticity analyses in their professional lives, and provides an introduction to the application of plasticity theories and basic continuum mechanics in metal forming processes. This book consists of three parts. The first part deals with the characteristics of plasticity and instability under simple tension or compression and plasticity in beam bending and torsion. The second part is designed to provide the basic principles of continuum mechanics, and the last part presents an extension of one-dimensional plasticity to general three-dimensional laws based on the fundamentals of continuum mechanics. Though most parts of the book are written in the context of general plasticity, the last two chapters are specifically devoted to sheet metal forming applications. The homework problems included are designed to reinforce understanding of the concepts involved. This book may be used as a textbook for a one semester course lasting fourteen weeks or longer. This book is intended to be self-sufficient such that readers can study it independently without taking another formal course. However, there are some prerequisites before starting this book, which include a course on engineering mathematics and an introductory course on solid mechanics.
Basics of Functional Analysis with Bicomplex Scalars, and Bicomplex Schur Analysis (SpringerBriefs in Mathematics)
by Michael Shapiro Daniel Alpay Maria Elena Luna-Elizarrarás Daniele C. StruppaThis book provides the foundations for a rigorous theory of functional analysis with bicomplex scalars. It begins with a detailed study of bicomplex and hyperbolic numbers and then defines the notion of bicomplex modules. After introducing a number of norms and inner products on such modules (some of which appear in this volume for the first time), the authors develop the theory of linear functionals and linear operators on bicomplex modules. All of this may serve for many different developments, just like the usual functional analysis with complex scalars and in this book it serves as the foundational material for the construction and study of a bicomplex version of the well known Schur analysis.
Basics of Image Processing: The Facts and Challenges of Data Harmonization to Improve Radiomics Reproducibility (Imaging Informatics for Healthcare Professionals)
by Ángel Alberich-Bayarri Fuensanta Bellvís-BatallerThis book, endorsed by EuSoMII, provides clinicians, researchers and scientists a useful handbook to navigate the intricate landscape of data harmonization, as we embark on a journey to improve the reproducibility, robustness and generalizability of multi-centric real-world data radiomic studies. In these pages, the authors delve into the foundational principles of radiomics and its far-reaching implications for precision medicine. They describe the different methodologies used in extracting quantitative features from medical images, the building blocks that enable the transformation of images into actionable predictions. This book sweeps from understanding the basis of harmonization to the implementation of all the knowledge acquired to date, with the aim of conveying the importance of harmonizing medical data and providing a useful guidance to enable its applicability and the future use of advanced radiomics-based models in routine clinical practice. As authors embark on this exploration of data harmonization in radiomics, they hope to ignite discussions, foster new ideas, and inspire researchers, clinicians, and scientists alike to embrace the challenges and opportunities that lie ahead. Together, they elevate radiomics as a reproducible technology and establish it as an indispensable and actionable tool in the quest for improved cancer diagnosis and treatment.
Basics of MATLAB and Beyond
by Andrew KnightMATLAB The tremendously popular computation, numerical analysis, signal processing, data analysis, and graphical software package-allows virtually every scientist and engineer to make better and faster progress. As MATLAB's world-wide sales approach a half-million with an estimated four million users, it becomes a near necessity that professionals a
Basics of Matrix Algebra for Statistics with R (Chapman & Hall/CRC The R Series #31)
by Nick FiellerA Thorough Guide to Elementary Matrix Algebra and Implementation in R Basics of Matrix Algebra for Statistics with R provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The book introduces the definition of a matrix and the basic rules of addition, subtraction, multiplication, and inversion. Later topics include determinants, calculation of eigenvectors and eigenvalues, and differentiation of linear and quadratic forms with respect to vectors. The text explores how these concepts arise in statistical techniques, including principal component analysis, canonical correlation analysis, and linear modeling. In addition to the algebraic manipulation of matrices, the book presents numerical examples that illustrate how to perform calculations by hand and using R. Many theoretical and numerical exercises of varying levels of difficulty aid readers in assessing their knowledge of the material. Outline solutions at the back of the book enable readers to verify the techniques required and obtain numerical answers. Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It prepares readers for higher-level and specialized studies in statistics.
Basics of Modern Mathematical Statistics: Exercises And Solutions (Springer Texts in Statistics)
by Thorsten Dickhaus Vladimir SpokoinyThis textbook provides a unified and self-contained presentation of the main approaches to and ideas of mathematical statistics. It collects the basic mathematical ideas and tools needed as a basis for more serious study or even independent research in statistics. The majority of existing textbooks in mathematical statistics follow the classical asymptotic framework. Yet, as modern statistics has changed rapidly in recent years, new methods and approaches have appeared. The emphasis is on finite sample behavior, large parameter dimensions, and model misspecifications. The present book provides a fully self-contained introduction to the world of modern mathematical statistics, collecting the basic knowledge, concepts and findings needed for doing further research in the modern theoretical and applied statistics. This textbook is primarily intended for graduate and postdoc students and young researchers who are interested in modern statistical methods.
Basics of Modern Mathematical Statistics: Exercises and Solutions (Springer Texts in Statistics)
by Wolfgang Karl Härdle Vladimir Spokoiny Vladimir Panov Weining WangThe complexity of today's statistical data calls for modern mathematical tools. Many fields of science make use of mathematical statistics and require continuous updating on statistical technologies. Practice makes perfect, since mastering the tools makes them applicable. Our book of exercises and solutions offers a wide range of applications and numerical solutions based on R. In modern mathematical statistics, the purpose is to provide statistics students with a number of basic exercises and also an understanding of how the theory can be applied to real-world problems. The application aspect is also quite important, as most previous exercise books are mostly on theoretical derivations. Also we add some problems from topics often encountered in recent research papers. The book was written for statistics students with one or two years of coursework in mathematical statistics and probability, professors who hold courses in mathematical statistics, and researchers in other fields who would like to do some exercises on math statistics.
Basics of Nonlinear Optimization: Around the Weierstrass Theorem (Compact Textbooks in Mathematics)
by Marek GalewskiThis textbook gives an introduction to optimization tools which arise around the Weierstrass theorem about the minimum of a lower semicontinuous function. Starting from a Euclidean space, it moves further into the infinite dimensional setting towards the direct variational method, going through differentiation and introducing relevant background information on the way. Exercises accompany the text and include observations, remarks, and examples that help understand the presented material. Although some basic knowledge of functional analysis is assumed, covering Hilbert and Banach spaces and the Lebesgue integration, the required background material is covered throughout the text, and literature suggestions are provided. For less experienced readers, a summary of some optimization techniques is also included. The book will appeal to both students and instructors in specialized courses on optimization, wishing to learn more about variational methods.
Basics of Optimization Theory (Synthesis Lectures on Mathematics & Statistics)
by Arthur David SniderThis book presents a short introduction to the main tools of optimization methodology including linear programming, steepest descent, conjugate gradients, and the Karush-Kuhn-Tucker-John conditions. Each topic is developed in terms of a specific physical model, so that the strategy behind every step is motivated by a logical, concrete, easily visualized objective. A quick perusal of the Fibonacci search algorithm provides a simple and tantalizing first encounter with optimization theory, and a review of the max-min exposition of one-dimensional calculus prepares readers for the more sophisticated topics found later in the book. Notable features are the innovative perspectives on the simplex algorithm and Karush-Kuhn-Tucker-John conditions as well as a wealth of helpful diagrams. The author provides pointers to references for readers who would like to learn more about rigorous definitions, proofs, elegant reformulations and extensions, and case studies. However, the book is sufficiently self-contained to serve as a reliable resource for readers who wish to exploit commercially available optimization software without investing the time to develop expertise in its aspects.This book also:Features innovative perspectives on the simplex algorithm and Krushal-Kuhn-Tucker-John conditionsServes as a resource for readers to use the tools of optimization without needing to acquire expertise in the theoryFeatures plentiful resources that focus on rigorous definitions, proofs, and case studies
Basics of Probability and Stochastic Processes
by Esra BasThis textbook explores probability and stochastic processes at a level that does not require any prior knowledge except basic calculus. It presents the fundamental concepts in a step-by-step manner, and offers remarks and warnings for deeper insights. The chapters include basic examples, which are revisited as the new concepts are introduced. To aid learning, figures and diagrams are used to help readers grasp the concepts, and the solutions to the exercises and problems. Further, a table format is also used where relevant for better comparison of the ideas and formulae. The first part of the book introduces readers to the essentials of probability, including combinatorial analysis, conditional probability, and discrete and continuous random variable. The second part then covers fundamental stochastic processes, including point, counting, renewal and regenerative processes, the Poisson process, Markov chains, queuing models and reliability theory. Primarily intended for undergraduate engineering students, it is also useful for graduate-level students wanting to refresh their knowledge of the basics of probability and stochastic processes.
Basics of Ramsey Theory
by Veselin JungićBasics of Ramsey Theory serves as a gentle introduction to Ramsey theory for students interested in becoming familiar with a dynamic segment of contemporary mathematics that combines ideas from number theory and combinatorics. The core of the of the book consists of discussions and proofs of the results now universally known as Ramsey’s theorem, van der Waerden’s theorem, Schur’s theorem, Rado’s theorem, the Hales–Jewett theorem, and the Happy End Problem of Erdős and Szekeres. The aim is to present these in a manner that will be challenging but enjoyable, and broadly accessible to anyone with a genuine interest in mathematics. Features Suitable for any undergraduate student who has successfully completed the standard calculus sequence of courses and a standard first (or second) year linear algebra course. Filled with visual proofs of fundamental theorems. Contains numerous exercises (with their solutions) accessible to undergraduate students. Serves as both a textbook or as a supplementary text in an elective course in combinatorics and aimed at a diverse group of students interested in mathematics.
Basiswissen Analysis: Eine Einführung mit Aufgaben, Lösungen, Selbsttests und interaktivem Online-Tool
by Burkhard LenzeDieses Buch bietet eine schlanke und gut zugängliche Hinführung zur Analysis. Gut 100 komplett durchgerechnete Beispiele, etwa 50 Aufgaben mit Lösungen sowie rund 40 kleine Selbsttests mit Antworten erleichtern den Zugang zum Thema. Abgerundet wird das Ganze durch etwa 80 Skizzen im Text sowie ein online verfügbares interaktives pdf-Tool zum Generieren von Zufallsaufgaben inklusive Lösungen. Das Buch richtet sich an Studierende in Studiengängen mit mathematischen Pflichtveranstaltungen im Grundstudium an Universitäten und Fachhochschulen. Es ist sowohl als Begleitlektüre für entsprechende Vorlesungen als auch zum Selbststudium optimal geeignet.
Basiswissen Angewandte Mathematik – Numerik, Grafik, Kryptik: Eine Einführung mit Aufgaben, Lösungen, Selbsttests und interaktivem Online-Tool
by Burkhard LenzeDieses Buch bietet eine schlanke und gut zugängliche Hinführung zur Angewandten Mathematik, speziell zur Numerischen Mathematik, Aspekten der Computer-Grafik sowie der Verschlüsselungstechnik. Rund 140 komplett durchgerechnete Beispiele, gut 100 Aufgaben mit Lösungen sowie etwa 50 Selbsttests mit Lösungen erleichtern den Zugang zum Thema. Abgerundet wird das Ganze durch etwa 80 Skizzen im Text sowie ein online verfügbares interaktives pdf-Tool zum Generieren von Zufallsaufgaben inklusive Lösungen. Das Buch richtet sich an Studierende in Studiengängen mit mathematischen Pflichtveranstaltungen im Grundstudium an Universitäten und Fachhochschulen. Es ist sowohl als Begleitlektüre für entsprechende Vorlesungen als auch zum Selbststudium optimal geeignet.
Basiswissen der mathematischen Bildbearbeitung: Zwischen Theorie und Anwendung (essentials)
by Anna BregerMithilfe dieses kompakten Buchs wird ein erstes strukturiertes Verständnis für die mathematischen Grundlagen digitaler Bilder und deren weitere Bearbeitung vermittelt. Ziel des Buchs ist es Interesse zu wecken und eine Basis zu geben um sich in Folge vertiefend mit digitaler und mathematischer Bildbearbeitung auseinander setzen zu können. Als alleinstehendes Werk ist es geeignet einen ersten Einblick in die Hintergründe der mittlerweile alltäglichen Bearbeitung von digitalen Bildern zu bekommen. Für das Verständnis der Inhalte ist ein elementares Wissen aus Linearer Algebra von Vorteil. Alle besprochenen Themen werden mathematisch motiviert und visuell dargestellt.
Basiswissen Lineare Algebra: Eine Einführung mit Aufgaben, Lösungen, Selbsttests und interaktivem Online-Tool
by Burkhard LenzeDieses Buch bietet eine schlanke und gut zugängliche Hinführung zur Linearen Algebra. Knapp 200 komplett durchgerechnete Beispiele, gut 100 Aufgaben mit Lösungen sowie rund 50 Selbsttests mit Lösungen erleichtern den Zugang zum Thema. Abgerundet wird das Ganze durch etwa 60 Skizzen im Text sowie ein online verfügbares interaktives pdf-Tool zum Generieren von Zufallsaufgaben inklusive Lösungen. Das Buch richtet sich an Studierende in Studiengängen mit mathematischen Pflichtveranstaltungen im Grundstudium an Universitäten und Fachhochschulen. Es ist sowohl als Begleitlektüre für entsprechende Vorlesungen als auch zum Selbststudium optimal geeignet.
Basiswissen Medizinische Statistik (Springer-Lehrbuch)
by Christel WeißÜbersichtlich und kompakt bietet Ihnen dieses Lehrbuch einen vollständigen Überblick über alle prüfungsrelevanten Inhalte der medizinischen Statistik. Es leitet Sie leicht verständlich und praxisbezogen durch das gesamte Basiswissen von den Grundlagen bis hin zu den wichtigsten Anwendungen. Profitieren Sie von der langjährigen Erfahrung der Dozentin, die sorgfältig das Wesentliche für Sie ausgewählt und aufbereitet hat.Der InhaltDas bewährte didaktische Konzept ermöglicht ein effizientes Lernen:Kernaussagen – Bringen das Wichtigste auf den PunktFallbeispiele – Stellen einen anschaulichen Bezug zur Praxis herPrüfungsteil – Für eine optimale Vorbereitung auf MC-Fragen und mündliche PrüfungenDie AutorinProf. Dr. sc. Hum. Habil. Dipl.- Math. Christel Weiß ist die Leiterin der Abteilung für Medizinische Statistik, Biomathematik und Informationsverarbeitung des Universitätsklinikums Mannheim, Medizinische Fakultät der Universität Heidelberg.
Basiswissen Statistik: Kompaktkurs für Anwender aus Wirtschaft, Informatik und Technik (Springer-Lehrbuch)
by Ansgar StelandIn diesem Buch werden in kompakter Form mithilfe zahlreicher Beispiele die #65533;blichen Modelle und Methoden der angewandten Wahrscheinlichkeitstheorie und Statistik dargestellt. Es ist daher insbesondere f#65533;r angehende Wirtschaftswissenschaftler, Ingenieure und Informatiker geeignet, welchen auch das didaktische Konzept des Buchs entgegenkommt: Verst#65533;ndnisfragen und Aufgaben in Form von ,,Meilensteinen" erleichtern das eigenst#65533;ndige #65533;berpr#65533;fen des Lernfortschritts. Ein ausf#65533;hrlicher mathematischer Anhang ,,Mathematik kompakt" stellt die wichtigsten Ergebnisse aus Analysis und linearer Algebra zum effizienten Nachschlagen zur Verf#65533;gung. Ein Glossar mit den wichtigsten englischen Begriffen sowie Tabellen der statistischen Testverteilungen runden die Darstellung ab.
Basiswissen Zahlentheorie: Eine Einführung in Zahlen und Zahlbereiche (Mathematik für das Lehramt)
by Kristina Reiss Gerald SchmiederKenntnisse über den Aufbau des Zahlensystems und über elementare zahlentheoretische Prinzipien gehören zum unverzichtbaren Grundwissen in der Mathematik. Das vorliegende Buch spannt den Bogen vom Rechnen mit natürlichen Zahlen über Teilbarkeitseigenschaften und Kongruenzbetrachtungen bis hin zu zahlentheoretischen Funktionen und Anwendungen wie der Kryptographie und Zahlencodierung. Wert wird dabei auf eine verständliche und umfassende Darstellung des Stoffes gelegt. Beweisideen, die hinter stringent durchgeführten Beweisen stehen und die Verknüpfung von Fachwissen mit Schulbezügen sind dabei als besondere Merkmale hervorzuheben. Ergänzt wird die Darstellung durch viele Übungsaufgaben, die mit Lösungshinweisen und vollständigen Lösungen versehen sind.
Basketball Data Science: With Applications in R (Chapman & Hall/CRC Data Science Series)
by Paola Zuccolotto Marica ManiseraUsing data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an MBA player&’s shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: · One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball. · Presents tools for modelling graphs and figures to visualize the data. · Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case. · Provides the source code and data so readers can do their own analyses on NBA teams and players.