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Gesamtkatalog

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Molchanov I: Risk Measures

Risk Measures

An Introduction to the Mathematical Theory

Professional Practice in Governance and Public Organizations

From Administrative Sources to Public Value

Data-Driven Learning in the EU

Learn to program more effectively, faster, with better results... and enjoy both the learning experience and the benefits it ultimately brings. This undergraduate-level textbook is motivated by Formal Methods, encouraging habits that lead to correct and concise computer programs; but its informal approach sidesteps reliance on Formal Logic that programmers are sometimes led to believe is required. Instead, a straightforward and intuitive use of simple 'What's true here' comments encourages precision of thought without prescription of notation. Drawing on decades of the author's experience in teaching/industry, the text's careful presentation concentrates on key principles of structuring and reasoning about programs, applying them first to small, understandable algorithms. Then students can concentrate on turning those reliably into their corresponding -and correct- program source-codes. The text includes over 200 exercises, with full solutions available online for instructors' use, plus mini-projects and automated quizzes to support instructors in building their own courses.

How to Write Programs That Work

Formal Methods, Informally

Tools and Frameworks for Managing People Risk and Increasing Resilience

Fundamentals of People Risk Management

This textbook offers an applied introduction to the methods of econometrics. Given the increasing importance of empirical analysis in science and the professional world, the book aims&nbsp;to move econometrics beyond&nbsp;its formal mathematical corner and make it accessible to a broader audience. In&nbsp;developing&nbsp;the textbook, the didactic profile was therefore given priority over scientific elegance. Supported by numerous illustrations, detailed verbal explanations, and accompanying numerical examples, both the&nbsp;fundamentals of econometric and&nbsp;more demanding topics are presented in an easily understandable way. The&nbsp;main sections of &nbsp;the Chapters&nbsp;do not use matrix algebra. However,&nbsp;in each chapter’s appendix, ambitious readers will find detailed matrix-algebra-based representations of the material covered in the main sections.

This textbook offers an applied introduction to the methods of econometrics. Given the increasing importance of empirical analysis in science and the professional world, the book aims&nbsp;to move econometrics beyond&nbsp;its formal mathematical corner and make it accessible to a broader audience. In&nbsp;developing&nbsp;the textbook, the didactic profile was therefore given priority over scientific elegance. Supported by numerous illustrations, detailed verbal explanations, and accompanying numerical examples, both the&nbsp;fundamentals of econometric and&nbsp;more demanding topics are presented in an easily understandable way. The&nbsp;main sections of &nbsp;the Chapters&nbsp;do not use matrix algebra. However,&nbsp;in each chapter’s appendix, ambitious readers will find detailed matrix-algebra-based representations of the material covered in the main sections.

An Introduction

Econometrics

World Scientific Series on Nonlinear Science Series A

Synchronization Of Systems With Time-delayed Coupling

Statistical Analysis with Python For Dummies

Cultivating Vitality, Presence, and Impact in a Changing World

Full Voice for Leaders

This book is intended to help people newly involved in the development of workplace safety and health programs to understand principles and concepts that can help them roll out what is often referred to as a "safety program". It introduces the safety and health landscape in simple terms and provides a framework for common program start-up or program improvement action steps.Providing small and medium sized enterprises (SMEs) with a primer on how to think about and go about creating a safety program, this book presents a higher-level overview, framework models and suggestions, resource information, and shares concepts that can help readers not only meet regulatory requirements but also provide true value to the organization. Safety consultant Greg G. Zigulis presents readers with an accessible overview of the types of things that should be known and considered in order to create and run an effective and sustainable health and safety program.Written for a broad professional readership, this book will be invaluable for all SME businesspersons and practitioners who need a seasoned expert to provide an understandable introduction to safety programs, whatever their situation. It's particularly relevant to start-ups and people given responsibility for workplace safety without a background in this area.

Setting Them Up and Making Them Work Effectively

Health and Safety Programs in Small and Medium-sized Businesses

A paradigm-shifting textbook that teaches graduate students in economics how to use economic models to interpret data. Graduate programs in economics often train students first in theory and econometrics, and then in more specialized fields of study, leaving fundamental aspects of how economists use theory to interpret data—concepts like falsifiability, identifiability, and counterfactual analysis—to be taught in niche, siloed contexts or not at all. Offering a new pedagogical paradigm, this textbook delivers a ready-made economics course covering the general concepts that unify different approaches to bringing economic models to data. Jesse Shapiro presents core ideas in quantitative economics as an abstract, cohesive whole and introduces canonical models that can be used across a wide range of applications. This course-in-a-book exposes students to stylized applications of these models that illuminate their foundations as well as recent research articles demonstrating the models’ broad applicability. <ul><li> Provides a coherent, generalized approach to making model-based inferences in empirical economics </li><li> Introduces central concepts and canonical models in quantitative economics </li><li> Features applications of modern research topics </li><li> Allows instructors to easily replicate novel approach of author’s popular Harvard course </li><li> Suits self-paced learning and classroom use alike </li></ul>

Introduction to Quantitative Economics

U.S. DataBook Series

The Handbook of U.S. Labor Statistics is recognized as an authoritative resource on the U.S. labor force. It continues and enhances the Bureau of Labor Statistics's (BLS) discontinued publication, Labor Statistics. It allows the user to understand recent developments as well as to compare today's economy with that of the past.This publication includes several tables throughout the book examining the extensive effect that coronavirus (COVID-19) has had on the labor market since 2020. In addition, it includes a completely updated chapter on prices and the most current employment projections through 2033.The Handbook is a comprehensive reference providing an abundance of information on a variety of topics. In addition to providing statistics on employment, unemployment, and prices, it includes information on topics such as:<ul><li>Earnings;</li><li>Productivity;</li><li>Consumer expenditures;</li><li>Occupational safety and health;</li><li>Union membership;</li><li>Working poor</li><li>Recent trends in the labor force</li><li>And much more!</li></ul> Features of the publication: In addition to over 215 tables that present practical data, the Handbook provides:<ul><li>Introductory material for each chapter that contains highlights of salient data and figures that call attention to noteworthy trends in the data</li><li>Notes and definitions, which contain concise descriptions of the data sources, concepts, definitions, and methodology from which the data are derived</li><li>References to more comprehensive reports which provide additional data and more extensive descriptions of estimation methods, sampling, and reliability measures</li></ul>

Employment, Earnings, Prices, Productivity, and Other Labor Data

Handbook of U.S. Labor Statistics 2025

Wiley Series in Probability and Statistics

New edition of a PROSE award finalist title on core concepts for machine learning, updated with the latest developments in the field, now with Python and R source code side-by-side Machine Learning is a comprehensive text on the core concepts, approaches, and applications of machine learning. It presents fundamental ideas, terminology, and techniques for solving applied problems in classification, regression, clustering, density estimation, and dimension reduction. New content for this edition includes chapter expansions which provide further computational and algorithmic insights to improve reader understanding. This edition also revises several chapters to account for developments since the prior edition. In this book, the design principles behind the techniques are emphasized, including the bias-variance trade-off and its influence on the design of ensemble methods, enabling readers to solve applied problems more efficiently and effectively. This book also includes methods for optimization, risk estimation, model selection, and dealing with biased data samples and software limitations - essential elements of most applied projects. Written by an expert in the field, this important resource: <ul> <li>Illustrates many classification methods with a single, running example, highlighting similarities and differences between methods</li> <li>Presents side-by-side Python and R source code which shows how to apply and interpret many of the techniques covered</li> <li>Includes many thoughtful exercises as an integral part of the text, with an appendix of selected solutions</li> <li>Contains useful information for effectively communicating with clients on both technical and ethical topics</li> <li>Details classification techniques including likelihood methods, prototype methods, neural networks, classification trees, and support vector machines</li> </ul> A volume in the popular Wiley Series in Probability and Statistics, Machine Learning offers the practical information needed for an understanding of the methods and application of machine learning for advanced undergraduate and beginner graduate students, data science and machine learning practitioners, and other technical professionals in adjacent fields.

A Concise Introduction

Machine Learning

Build protection from third-party and supply chains risks with this practical guide to developing an enterprise-wide approach to resilience.

An Enterprise-wide Approach to Resilience

Risk Management for Third Parties and Supply Chains

Risk Measures

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