Download and read online Bayes Rule in PDF and EPUB In this richly illustrated book, a range of accessible examples are used to show how Bayes' rule is actually a natural consequence of commonsense reasoning. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for the novice who wishes to become familiar with the basic principles of Bayesian analysis.
Download and read online Bayes Rule With R in PDF and EPUB Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this book includes R (3.2) code snippets, which reproduce key numerical results and diagrams.
Download and read online Bayes Rule with MatLab in PDF and EPUB Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and Python programs provided online. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this MatLab version of Bayes' Rule includes working MatLab code snippets alongside the relevant equations.
Download and read online Bayes Rule with Python in PDF and EPUB Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis. Note that this book includes Python (3.0) code snippets, which reproduce key numerical results and diagrams.
Download and read online Statistik Klassisch oder Bayes in PDF and EPUB Die schließende Statistik ist die Wissenschaft davon, aus einer Stichprobe auf die Gesamtheit zu schließen. In ihr gibt es zwei vorherrschende Lehren: die klassische Statistik und die Bayes-Statistik. Die klassische Statistik verwendet zum Schätzen von Parametern und zum Testen von Hypothesen nur die Stichprobe; die bayessche stellt zusätzlich in Rechnung, was man sonst noch über das Problem weiß oder annimmt. Das hängt mit unterschiedlichen Meinungen darüber zusammen, was Wahrscheinlichkeit bedeutet: relative Häufigkeit in Zufallsexperimenten (die klassische Sicht) oder einen Ausdruck des Wissens (die bayessche). Dieses Buch soll die Standpunkte klären und prüfen: Ausgehend vom jeweiligen Wahrscheinlichkeitsbegriff werden klassische und bayessche Methoden entwickelt und auf Schätz- und Testprobleme angewandt, wobei Gemeinsamkeiten und Unterschiede hervorgehoben werden und besonderes Augenmerk auf die Interpretation der Ergebnisse gerichtet ist.
Download and read online Programmieren lernen mit Python in PDF and EPUB Python ist eine moderne, interpretierte, interaktive und objektorientierte Skriptsprache, vielseitig einsetzbar und sehr beliebt. Mit mathematischen Vorkenntnissen ist Python leicht erlernbar und daher die ideale Sprache für den Einstieg in die Welt des Programmierens. Das Buch führt Sie Schritt für Schritt durch die Sprache, beginnend mit grundlegenden Programmierkonzepten, über Funktionen, Syntax und Semantik, Rekursion und Datenstrukturen bis hin zum objektorientierten Design. Zur aktualisierten Auflage Diese Auflage behandelt Python 3, geht dabei aber auch auf Unterschiede zu Python 2 ein. Außerdem wurde das Buch um die Themen Unicode, List und Dictionary Comprehensions, den Mengen-Typ Set, die String-Format-Methode und print als Funktion ergänzt. Jenseits reiner Theorie Jedes Kapitel enthält passende Übungen und Fallstudien, kurze Verständnistests und kleinere Projekte, an denen Sie die neu erlernten Programmierkonzepte gleich ausprobieren und festigen können. Auf diese Weise können Sie das Gelernte direkt anwenden und die jeweiligen Programmierkonzepte nachvollziehen. Lernen Sie Debugging-Techniken kennen Am Ende jedes Kapitels finden Sie einen Abschnitt zum Thema Debugging, der Techniken zum Aufspüren und Vermeiden von Bugs sowie Warnungen vor entsprechenden Stolpersteinen in Python enthält.
Download and read online Introduction to statistics and data analysis for physicists in PDF and EPUB
Download and read online Gleichwertigkeit von Termen in PDF and EPUB Larissa Zwetzschler geht der Frage nach, wie die in der Forschung häufig beschriebenen Verstehensschwierigkeiten von algebraischen Termen und Termumformungen überwunden werden können und wie der Aufbau von tragfähigen inhaltlichen Vorstellungen zur Gleichwertigkeit von Termen unterstützt werden kann. Die Autorin hat einen Prototyp eines Lehr-Lernarrangements entwickelt und unterschiedliche Entwicklungslinien beim Vorstellungsaufbau herausgearbeitet.
Download and read online Processes of Believing The Acquisition Maintenance and Change in Creditions in PDF and EPUB This volume answers the question: Why do we believe what we believe? It examines current research on the concept of beliefs, and the development in our understanding of the process of believing. It takes into account empirical findings in the field of neuroscience regarding the processes that underlie beliefs, and discusses the notion that beyond the interactive exploratory analysis of sensory information from the complex outside world, humans engage in an evaluative analysis by which they attribute personal meaning and relevance to the probabilistic representations of objects and events. Beliefs exert a strong influence on behaviour, decision-making, and identifying and solving problems. Despite their importance, beliefs have until recently not been at the centre of scientific interest. In fact, “belief” is an ill-defined phenomenon. From a transdisciplinary perspective the actual approaches to understanding belief seem incompatible as they attempt to highlight such different topics as “belief – religion”, “belief – spirituality”, “belief – faith”, “belief – knowledge”, “belief – attitude”, “belief – disbelief”, “belief – illusion”, and “believing – brain function”. This situation contradicts the idea that belief is close to pathological phenomena and that it should be eliminated from scientific discussions. Rather, believing is fundamental for understanding the many problems of every-day life. In fact, the book shows that beliefs are relevant for politics, international affairs, economy, law, or religions also in modern societies. This book presents the increasing scientific interest in beliefs and believing, and reflects the change in focus from the content aspect of belief towards the fluid nature of believing.
Download and read online An Adventure in Statistics in PDF and EPUB Shortlisted for the British Book Design and Production Awards 2016 Shortlisted for the Association of Learned & Professional Society Publishers Award for Innovation in Publishing 2016 An Adventure in Statistics: The Reality Enigma by best-selling author and award-winning teacher Andy Field offers a better way to learn statistics. It combines rock-solid statistics coverage with compelling visual story-telling to address the conceptual difficulties that students learning statistics for the first time often encounter in introductory courses - guiding students away from rote memorization and toward critical thinking and problem solving. Field masterfully weaves in a unique, action-packed story starring Zach, a character who thinks like a student, processing information, and the challenges of understanding it, in the same way a statistics novice would. Illustrated with stunning graphic novel-style art and featuring Socratic dialogue, the story captivates readers as it introduces them to concepts, eliminating potential statistics anxiety. The book assumes no previous statistics knowledge nor does it require the use of data analysis software. It covers the material you would expect for an introductory level statistics course that Field’s other books (Discovering Statistics Using IBM SPSS Statistics and Discovering Statistics Using R) only touch on, but with a contemporary twist, laying down strong foundations for understanding classical and Bayesian approaches to data analysis. In doing so, it provides an unrivalled launch pad to further study, research, and inquisitiveness about the real world, equipping students with the skills to succeed in their chosen degree and which they can go on to apply in the workplace. The Story and Main Characters The Reality Revolution In the City of Elpis, in the year 2100, there has been a reality revolution. Prior to the revolution, Elpis citizens were unable to see their flaws and limitations, believing themselves talented and special. This led to a self-absorbed society in which hard work and the collective good were undervalued and eroded. To combat this, Professor Milton Grey invented the reality prism, a hat that allowed its wearers to see themselves as they really were - flaws and all. Faced with the truth, Elpis citizens revolted and destroyed and banned all reality prisms. The Mysterious Disappearance Zach and Alice are born soon after all the prisms have been destroyed. Zach, a musician who doesn’t understand science, and Alice, a geneticist who is also a whiz at statistics, are in love. One night, after making a world-changing discovery, Alice suddenly disappears, leaving behind a song playing on a loop and a file with her research on it. Statistics to the Rescue! Sensing that she might be in danger, Zach follows the clues to find her, as he realizes that the key to discovering why Alice has vanished is in her research. Alas! He must learn statistics and apply what he learns in order to overcome a number of deadly challenges and find the love of his life. As Zach and his pocket watch, The Head, embark on their quest to find Alice, they meet Professor Milton Grey and Celia, battle zombies, cross a probability bridge, and encounter Jig:Saw, a mysterious corporation that might have something to do with Alice’s disappearance… Author News "Eight years ago I had the idea to write a fictional story through which the student learns statistics via a shared adventure with the main character..." Read the complete article from Andy Field on writing his new book Times Higher Education article: “Andy Field takes statistics adventure to a new level” Stay Connected Connect with us on Facebook and share your experiences with Andy’s texts, check out news, access free stuff, see photos, watch videos, learn about competitions, and much more. Video Links Go behind the scenes and learn more about the man behind the book: Watch Andy talk about why he created a statistics book using the framework of a novel and illustrations by one of the illustrators for the show, Doctor Who. See more videos on Andy’s YouTube channel Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.
Download and read online Schnelles Denken langsames Denken in PDF and EPUB Intuition oder Vernunft? - Menschliches Verhalten und das Verständnis von Wirtschaft Wie treffen wir unsere Entscheidungen? Warum ist Zögern ein überlebensnotwendiger Reflex, und was passiert in unserem Gehirn, wenn wir andere Menschen oder Dinge beurteilen? Daniel Kahneman, Nobelpreisträger und einer der einflussreichsten Wissenschaftler unserer Zeit, zeigt anhand ebenso nachvollziehbarer wie verblüffender Beispiele, welchen mentalen Mustern wir folgen und wie wir uns gegen verhängnisvolle Fehlentscheidungen wappnen können.
Download and read online Philosophy and the Sciences for Everyone in PDF and EPUB What is the origin of our universe? What are dark matter and dark energy? What is our role in the universe as human beings capable of knowledge? What makes us intelligent cognitive agents seemingly endowed with consciousness? Scientific research across both the physical and cognitive sciences raises fascinating philosophical questions. Philosophy and the Sciences For Everyone introduces these questions and more. It begins by asking what good is philosophy for the sciences before examining the following questions: The origin of our universe Dark matter and dark energy Anthropic reasoning in philosophy and cosmology Evolutionary theory and the human mind What is consciousness? Intelligent machines and the human brain Embodied Cognition. Each chapter includes an introduction, summary and study questions and there is a glossary of technical terms. Designed to be used on the corresponding Philosophy and the Sciences online course offered by the University of Edinburgh this book is also a superb introduction to central topics in philosophy of science and popular science.
Download and read online The Image Processing Handbook Seventh Edition in PDF and EPUB Consistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more. Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines Presents 500+ entirely new figures and images, with more than two-thirds appearing in color The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.
Download and read online Uncertainty Analysis of Experimental Data with R in PDF and EPUB "This would be an excellent book for undergraduate, graduate and beyond....The style of writing is easy to read and the author does a good job of adding humor in places. The integration of basic programming in R with the data that is collected for any experiment provides a powerful platform for analysis of data.... having the understanding of data analysis that this book offers will really help researchers examine their data and consider its value from multiple perspectives – and this applies to people who have small AND large data sets alike! This book also helps people use a free and basic software system for processing and plotting simple to complex functions." Michelle Pantoya, Texas Tech University Measurements of quantities that vary in a continuous fashion, e.g., the pressure of a gas, cannot be measured exactly and there will always be some uncertainty with these measured values, so it is vital for researchers to be able to quantify this data. Uncertainty Analysis of Experimental Data with R covers methods for evaluation of uncertainties in experimental data, as well as predictions made using these data, with implementation in R. The books discusses both basic and more complex methods including linear regression, nonlinear regression, and kernel smoothing curve fits, as well as Taylor Series, Monte Carlo and Bayesian approaches. Features: 1. Extensive use of modern open source software (R). 2. Many code examples are provided. 3. The uncertainty analyses conform to accepted professional standards (ASME). 4. The book is self-contained and includes all necessary material including chapters on statistics and programming in R. Benjamin D. Shaw is a professor in the Mechanical and Aerospace Engineering Department at the University of California, Davis. His research interests are primarily in experimental and theoretical aspects of combustion. Along with other courses, he has taught undergraduate and graduate courses on engineering experimentation and uncertainty analysis. He has published widely in archival journals and became an ASME Fellow in 2003. ?
Download and read online Regression Models for Categorical Count and Related Variables in PDF and EPUB Social science and behavioral science students and researchers are often confronted with data that are categorical, count a phenomenon, or have been collected over time. Sociologists examining the likelihood of interracial marriage, political scientists studying voting behavior, criminologists counting the number of offenses people commit, health scientists studying the number of suicides across neighborhoods, and psychologists modeling mental health treatment success are all interested in outcomes that are not continuous. Instead, they must measure and analyze these events and phenomena in a discrete manner. This book provides an introduction and overview of several statistical models designed for these types of outcomes—all presented with the assumption that the reader has only a good working knowledge of elementary algebra and has taken introductory statistics and linear regression analysis. Numerous examples from the social sciences demonstrate the practical applications of these models. The chapters address logistic and probit models, including those designed for ordinal and nominal variables, regular and zero-inflated Poisson and negative binomial models, event history models, models for longitudinal data, multilevel models, and data reduction techniques such as principal components and factor analysis. Each chapter discusses how to utilize the models and test their assumptions with the statistical software Stata, and also includes exercise sets so readers can practice using these techniques. Appendices show how to estimate the models in SAS, SPSS, and R; provide a review of regression assumptions using simulations; and discuss missing data. A companion website includes downloadable versions of all the data sets used in the book.