Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You'll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. What You'll Learn Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).

This easy-to-follow textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling. The text describes the mathematical theory alongside the basic concepts and methods of numerical analysis, enriched by computer experiments using MATLAB, Python, Maple, and Java applets. This fully updated and expanded new edition also features an even greater number of programming exercises. Topics and features: describes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves; discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation (NEW); contains experiments, exercises, definitions, and propositions throughout the text; supplies programming examples in Python, in addition to MATLAB (NEW); provides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material. Addressing the core needs of computer science students and researchers, this clearly written textbook is an essential resource for undergraduate-level courses on numerical analysis, and an ideal self-study tool for professionals seeking to enhance their analysis skills.

Der neuartige Einstieg in Digitale Medien fur die Mathematikdidaktik der Sekundarstufen, keine (zu) enge Bindung an spezifische Hard- oder Software Systematische und umfassende Darstellung von Grund auf mit Anregungen fur den Mathematikunterricht, gezielt fur das Lehramtsstudium und die Schulpraxis Die vielfaltigen Erprobungen an der Universitat Bielefeld, am Studienseminar Hamm und in der Lehrerfortbildung bilden eine gute Grundlage fur den Erfolg dieses Bandes

Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data.

Das Programmpaket SAS hat sich im Lauf der Jahre als Standardprogramm zur statistischen Datenanalyse etabliert. Der souverane Umgang mit statistischen Methoden und deren praktischer Umsetzung in SAS bietet somit einen unschatzbaren Vorteil fur die tagliche Arbeit des Datenanalytikers. Im vorliegenden Buch erlernt der Leser zunachst die Grundlagen fur die Programmierung. Anschliessend wird eine grosse Auswahl statistischer Verfahren und deren Umsetzung als SAS-Programm vorgestellt. Dabei wird grosses Augenmerk auf die grafischen Aspekte der statistischen Datenanalyse gelegt. Ein zusatzlicher Teil uber Programmierung mit IML und Makros sowie hilfreiche Assistenten in SAS runden die Darstellung ab. Mit seiner umfassenden Themenauswahl ist das Buch als Einfuhrung, aber auch als Nachschlagewerk fur den fortgeschritteneren Leser geeignet.

Dieses Lehrbuch motiviert und erklart die Inhalte der deskriptiven und induktiven Statistik, indem es die mathematischen Grundlagen der Statistik mit vielfaltigen, leicht nachvollziehbaren Anwendungen und Beispielen verbindet: Durch uberschaubare Beispiele, die mit Papier und Stift durchgerechnet werden koennen (und sollten!) gewinnt der Leser zunachst Verstandnis und einen routinierten Umgang mit den zentralen Formeln. Fur groessere Beispiele kommt das frei verfugbare statistische Software R zum Einsatz, welches die Berechnungen schnell und verlasslich auch fur grosse Datensatze umsetzt.

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R.

"Its biggest advantage is that it aims only to teach R...It organizes R commands very efficiently, with much teaching guidance included. I would describe this book as being handy--it's the kind of book that you want to keep in your jacket pocket or backpack all the time, ready for use, like a Swiss Army knife." (Loveday Conquest, University of Washington)

"Whilst several books focus on learning statistics in R..., the authors of this book fill a gap in the market by focusing on learning R whilst almost completely avoiding any statistical jargon...The fact that the authors have very extensive experience of teaching R to absolute beginners shines throughout." (Mark Mainwaring, Lancaster University)

"Exactly what is needed...This is great, nice work. I love the ecological/biological examples; they will be an enormous help." (Andrew J. Tyne, University of Nebraska-Lincoln)

R is now the most widely used statistical package/language in university statistics departments and many research organisations. Its great advantages are that for many years it has been the leading-edge statistical package/language and that it can be freely downloaded from the R web site. Its cooperative development and open code also attracts many contributors meaning that the modelling and data analysis possibilities in R are much richer than in GLIM4, and so the R edition can be substantially more comprehensive than the GLIM4 edition of Statistical Modelling. This text provides a comprehensive treatment of the theory of statistical modelling in R with an emphasis on applications to practical problems and an expanded discussion of statistical theory. A wide range of case studies is provided, using the normal, binomial, Poisson, multinomial, gamma, exponential and Weibull distributions, making this book ideal for graduates and research students in applied statistics and a wide range of quantitative disciplines.

This is the first book to present time series analysis using the SAS Enterprise Guide software. It includes some starting background and theory to various time series analysis techniques, and demonstrates the data analysis process and the final results via step-by-step extensive illustrations of the SAS Enterprise Guide software. This book is a practical guide to time series analyses in SAS Enterprise Guide, and is valuable resource that benefits a wide variety of sectors.

Schwerpunkt auf Simulation und grafischer Darstellung der Resultate Angereichert mit Praxisbeispielen und Reflexionsaufgaben Datensatze, Programmcodes und Loesungen online verfugbar

This is a new edition of the accessible and student-friendly 'how to' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from 'zero to hero', updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more. Revised and updated, each chapter includes: example data and commands to explore hands-on; scripts and coding to exemplify specific functionality; self-contained exercises for students to work through; embedded code within the descriptive text. The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.

Dieses Buch liefert Anfangern einen leichten Einstieg in SPSS und dient erfahrenen Nutzern (auch fruherer Programmversionen) zugleich als hervorragendes Nachschlagewerk. Die Nutzung des Buchs ist dabei weitgehend ohne mathematische Vorkenntnisse moeglich. Die Methoden und deren Anwendung mit SPSS werden anschaulich anhand von Beispielen aus der Praxis erlautert. Auf der Internetseite zum Buch sind alle Datensatze, erganzende Texte, UEbungsaufgaben mit ihren Loesungen sowie weitere Informationen verfugbar. Die 9. Auflage dieses Buchs basiert auf IBM SPSS Statistics 24 (Base und Exact Tests). Im Rahmen der Neuauflage wurden etliche Kapitel uberarbeitet. Hinzugekommen sind Kapitel zu neuen statistischen Verfahren sowie ein UEbersichtskapitel zu Signifikanztests: Letzteres erleichtert es dem SPSS-Nutzer, aus der Vielzahl der in SPSS verfugbaren Tests den fur seine Aufgabenstellung richtigen zu wahlen.

Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the stress testing process. An introduction to multivariate time series modeling paves the way to scenario analysis in order to assess a bank resilience against adverse macroeconomic conditions. Assets and liabilities are jointly studied to highlight the key issues that a risk manager needs to face. A multi-national bank prototype is used all over the book for diving into market, credit, and operational stress testing. Interest rate, liquidity and other major risks are also studied together with the former to outline how to implement a fully integrated risk management toolkit. Examples, business cases, and exercises worked in Matlab and R facilitate readers to develop their own models and methodologies.

Since 1984, Geophysical Data Analysis has filled the need for a short, concise reference on inverse theory for individuals who have an intermediate background in science and mathematics. The new edition maintains the accessible and succinct manner for which it is known, with the addition of: MATLAB examples and problem sets Advanced color graphics Coverage of new topics, including Adjoint Methods; Inversion by Steepest Descent, Monte Carlo and Simulated Annealing methods; and Bootstrap algorithm for determining empirical confidence intervals

Building SPSS Graphs to Understand Data is for anyone needing to understand large or small amounts of data. It describes how to build and interpret graphs, showing how understanding data means that the graph must clearly and succinctly answer questions about the data. In 16 of the 19 chapters research questions are presented, and the reader builds the appropriate graph needed to answer the questions. This handy guide can be used in conjunction with any introductory or intermediate statistics book where the focus is on in-depth presentation of how graphs are used. This book will also useful for graduate students doing research at the masters or doctoral level. The book also contains a chapter designed to address many of the ways that graphs can be used to mislead the graph reader.

Proof and Disproof in Formal Logic is a lively and entertaining introduction to formal logic providing an excellent insight into how a simple logic works. Formal logic allows you to check a logical claim without considering what the claim means. This highly abstracted idea is an essential
and practical part of computer science. The idea of a formal system-a collection of rules and axioms, which define a universe of logical proofs-is what gives us programming languages and modern-day programming. This book concentrates on using logic as a tool: making and using formal proofs and
disproofs of particular logical claims. The logic it uses-natural deduction-is very small and very simple; working with it helps you see how large mathematical universes can be built on small foundations. The book is divided into four parts:
Part I "Basics" gives an introduction to formal logic with a short history of logic and explanations of some technical words.
Part II "Formal Syntactic Proof" show you how to do calculations in a formal system where you are guided by shapes and never need to think about meaning. Your experiments are aided by Jape, which can operate as both inquisitor and oracle.
Part III "Formal Semantic Disproof" shows you how to construct mathematical counterexamples to shoe that proof is impossible. Jape can check the counterexamples you build.
Part IV" Program Specification and Proof" describes how to apply your logical understanding to a real computer science problem, the accurate description and verification of programs. Jape helps, as far as arithmetic allows.
Aimed at undergraduates and graduates in computer science, logic, mathematics and philosophy, thetext includes reference to and exercises based on the computer software package Jape, an interactive teaching and research tool designed and hosted by the author that is freely available on the
web.

Proof and Disproof in Formal Logic is a lively and entertaining introduction to formal logic providing an excellent insight into how a simple logic works. Formal logic allows you to check a logical claim without considering what the claim means. This highly abstracted idea is an essential and practical part of computer science. The idea of a formal system-a collection of rules and axioms, which define a universe of logical proofs-is what gives us programming languages and modern-day programming. This book concentrates on using logic as a tool: making and using formal proofs and disproofs of particular logical claims. The logic it uses-natural deduction-is very small and very simple; working with it helps you see how large mathematical universes can be built on small foundations. The book is divided into four parts:
Part I "Basics" gives an introduction to formal logic with a short history of logic and explanations of some technical words.
Part II "Formal Syntactic Proof" show you how to do calculations in a formal system where you are guided by shapes and never need to think about meaning. Your experiments are aided by Jape, which can operate as both inquisitor and oracle.
Part III "Formal Semantic Disproof" shows you how to construct mathematical counterexamples to shoe that proof is impossible. Jape can check the counterexamples you build.
Part IV" Program Specification and Proof" describes how to apply your logical understanding to a real computer science problem, the accurate description and verification of programs. Jape helps, as far as arithmetic allows.
Aimed at undergraduates and graduates in computer science, logic, mathematics and philosophy, thetext includes reference to and exercises based on the computer software package Jape, an interactive teaching and research tool designed and hosted by the author that is freely available on the web.

Matrix Algorithms in MATLAB focuses on the MATLAB code implementations of matrix algorithms. The MATLAB codes presented in the book are tested with thousands of runs of MATLAB randomly generated matrices, and the notation in the book follows the MATLAB style to ensure a smooth transition from formulation to the code, with MATLAB codes discussed in this book kept to within 100 lines for the sake of clarity. The book provides an overview and classification of the interrelations of various algorithms, as well as numerous examples to demonstrate code usage and the properties of the presented algorithms. Despite the wide availability of computer programs for matrix computations, it continues to be an active area of research and development. New applications, new algorithms, and improvements to old algorithms are constantly emerging.

Dieses Buch bietet einen historisch orientierten Einstieg in die Algorithmik, also die Lehre von den Algorithmen, in Mathematik, Informatik und daruber hinaus. Besondere Merkmale und Zielsetzungen sind: Elementaritat und Anschaulichkeit, die Berucksichtigung der historischen Entwicklung, Motivation der Begriffe und Verfahren anhand konkreter, aussagekraftiger Beispiele unter Einbezug moderner Werkzeuge (Computeralgebrasysteme, Internet). Als Zusatzmedien werden computer- und internetspezifische Interaktions- und Visualisierungsmoeglichkeiten (kostenlos) zur Verfugung gestellt. Das Werk wendet sich an Studierende und Lehrende an Schulen und Hochschulen sowie an Nichtspezialisten, die an den Themen "Computer/Algorithmen/Programmierung" einschliesslich ihrer historischen und geisteswissenschaftlichen Dimension interessiert sind.

Berthold Heinrich stellt die mathematischen und zeichnerischen Grundlagen fur die Darstellung von Objekten im Raum auf kariertem Papier vor. Dabei prasentiert er auch die Nutzung von Software. In der Schule wird oft kariertes Papier als Raster zur Darstellung von Flachen und Koerpern genutzt. Allerdings werden, selbst in einigen Druckwerken, z.B. die entstehenden Ellipsen und Winkelboegen ungenau gezeichnet oder eine Kugelkontur falsch als Kreis dargestellt. Im vorliegenden Essential werden die korrekten Verfahren sowohl theoretisch als auch an konkreten Beispielen vorgestellt und koennen meist direkt umgesetzt werden. Einige aufwandigere Ablaufe stellt der Autor anschaulich an Beispielen dar.

This textbook introduces the vast array of features and powerful mathematical functions of Mathematica using a multitude of clearly presented examples and worked-out problems. Each section starts with a description of a new topic and some basic examples. The author then demonstrates the use of new commands through three categories of problems - the first category highlights those essential parts of the text that demonstrate the use of new commands in Mathematica whilst solving each problem presented; - the second comprises problems that further demonstrate the use of commands previously introduced to tackle different situations; and - the third presents more challenging problems for further study. The intention is to enable the reader to learn from the codes, thus avoiding long and exhausting explanations. While based on a computer algebra course taught to undergraduate students of mathematics, science, engineering and finance, the book also includes chapters on calculus and solving equations, and graphics, thus covering all the basic topics in Mathematica. With its strong focus upon programming and problem solving, and an emphasis on using numerical problems that do not need any particular background in mathematics, this book is also ideal for self-study and as an introduction to researchers who wish to use Mathematica as a computational tool. This new edition has been extensively revised and updated, and includes new chapters with problems and worked examples.

Wie koennen grosse und kleine Datenmengen aus Beobachtungen, Messungen, Befragungen, Untersuchungen, Analysen etc. verwaltet, aufbereitet, komprimiert, mit Kennzahlen erklart und wirksam grafisch dargestellt werden? Wie kann man dazu Hypothesen prufen, Zusammenhange aufdecken, Abhangigkeiten finden? Dieses Buch zeigt Ihnen, wie die grundlegenden Methoden der Statistik recht einfach mit Excel umsetzbar sind. Es wurden in einheitlicher, sehr verstandlicher Methodik die grundlegenden statistischen Verfahren sowohl der beschreibenden als auch der beurteilenden Statistik zusammengestellt. Umfangreiche Beispiele, didaktisch aufbereitet und stets ausfuhrlich mit Excel umgesetzt, bieten eine umfassende Hilfe fur den Umgang mit Datenmengen. Alle Beispiele stehen online fur individuelle UEbungen bereit.

Der Leser wird von der Untersuchung und Darstellung empirisch vorgefundener Daten bis zu Planung und Auswertung eigener statistischer Versuchsplane durch dieses Buch begleitet. Es wird dabei ganz bewusst auf praktisch relevante und bewahrte Methoden Bezug genommen und auf weiterfuhrende wissenschaftliche Beschreibungen verzichtet. Praktisch relevante Methoden werden im Zusammenhang dargestellt."

Dieser Band mit Beitragen aus der nationalen und internationalen Forschung zum 60. Geburtstag von Prof. Dr. Rolf Biehler (Universitat Paderborn) prasentiert wissenschaftliche Arbeiten zum Werkzeugeinsatz beim Lehren und Lernen von Mathematik im Allgemeinen sowie von Statistik und Stochastik im Besonderen. Wie ein roter Faden durchzieht den Festband, wie auch schon das wissenschaftliche Oeuvre von Rolf Biehler, ein breites Verstandnis des Begriffs Werkzeug (engl. tools ). Die Themen decken das komplette Spektrum der Mathematikdidaktik auf allen Schulstufen sowie auf dem tertiaren Sektor ab. Es gibt Beitrage zum Einsatz von Tools in der Grundschule, ebenso wie aus den Sekundarstufen, der Hochschule und der Lehreraus- und -weiterbildung. Im Band werden sowohl Beispiele zum konkreten Einsatz von Werkzeugen im Unterricht aufgezeigt, als auch Studien zur Wirksamkeit von Werkzeugen im Kontext von Mathematiklernen, theoretische Artikel zum Einsatz von Werkzeugen und Neuentwicklungen von Werkzeug-Software vorgelegt.

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"MATLAB for Neuroscientists" serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment.

This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels-advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills-will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners.
The first complete volume on MATLAB focusing on neuroscience and psychology applicationsProblem-based approach with many examples from neuroscience and cognitive psychology using real dataIllustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience