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Privault N: Financial Risk Analytics

Financial Risk Analytics

A Mathematical Introduction with R and Python

Build an AI security operating model that manages risk, strengthens governance and enables AI to scale securely. AI Risk Management is a practical guide for AI risk owners, GRC managers, AI governance managers and technology risk professionals responsible for managing the security risks of AI.Written by security expert Rafah Knight, this book shows how to make AI security operational, measurable and embedded into existing business processes. It provides practical guidance on establishing ownership and accountability for AI risk, designing effective governance structures, implementing policies and controls and managing third-party AI vendor exposure.Drawing on real-world examples from financial services, retail, the public sector and healthcare, learn how to: - Build an effective AI security operating model - Establish clear ownership and accountability for AI risk - Design AI governance policies, controls and assurance processes - Measure AI security and operational risks effectively - Manage third-party AI vendor exposure at scaleAI Security gives you the practical structures and controls to operationalize AI assurance, strengthen AI governance and support secure AI adoption at scale.Themes include: AI security, AI risk management, AI governance, GRC, AI assurance, third-party AI risk

How to Scale AI Securely

AI Risk Management

International Series in Operations Research & Management Science

This innovative book explores methodologies for constructing confidence intervals for proportions. It compares existing techniques and introduces new procedures developed by the authors, emphasizing the actual coverage function to assess their effectiveness. It covers various applications, such as estimating success rates in Monte Carlo simulations, gauging electoral support, assessing project completion rates, and evaluating product reliability. It provides analysts with both point and interval estimators, highlighting how interval estimators offer precision for point estimates.

Key focus is placed on selecting appropriate confidence interval procedures and understanding their statistical properties. While traditional methods offer only approximate intervals, this work examines popular options and derives their statistical characteristics, providing guidelines for practitioners. Additionally, it discusses pointwise confidence intervals for survivor functions from randomly right-censored datasets, appealing to reliability engineers and survival analysts. It includes practical applications through functions in R, allowing practitioners to compute confidence intervals and visualize their coverage.

As the first of its kind to focus solely on this topic, the book serves as a valuable resource for advanced students and can support a one-semester course on confidence intervals for proportions, making a significant contribution to the field of statistics.

This innovative book explores methodologies for constructing confidence intervals for proportions. It compares existing techniques and introduces new procedures developed by the authors, emphasizing the actual coverage function to assess their effectiveness. It covers various applications, such as estimating success rates in Monte Carlo simulations, gauging electoral support, assessing project completion rates, and evaluating product reliability. It provides analysts with both point and interval estimators, highlighting how interval estimators offer precision for point estimates.Key focus is placed on selecting appropriate confidence interval procedures and understanding their statistical properties. While traditional methods offer only approximate intervals, this work examines popular options and derives their statistical characteristics, providing guidelines for practitioners. Additionally, it discusses pointwise confidence intervals for survivor functions from randomly right-censored datasets, appealing to reliability engineers and survival analysts. It includes practical applications through functions in R, allowing practitioners to compute confidence intervals and visualize their coverage.As the first of its kind to focus solely on this topic, the book serves as a valuable resource for advanced students and can support a one-semester course on confidence intervals for proportions, making a significant contribution to the field of statistics.

Analysis of Binary Data with Applications to Survival Analysis

Confidence Intervals for Proportions

This book presents advanced mathematical programming models for contemporary supply chain risk optimization problems. It focuses on cutting‑edge issues such as supply chain viability under long‑term disruption risks, including reshoring decisions; optimization of digital supply chain cybersecurity and physical resilience in cyber‑physical supply chains; and supply chain fairness with respect to cost–service trade‑offs, profit distribution, and the allocation of cybersecurity investments. It also introduces computationally efficient decision‑making frameworks for emerging challenges in global supply chain management, including the reduction of cyber and physical risks and the enhancement of resilience and fairness. Each chapter ends with a table summarizing major managerial insights and the end-of-chapter problems to help the reader a self-check of material comprehension and to encourage for a further self-study.The book is intended for practitioners, researchers, and master’s and PhD‑level students in supply chain management, industrial engineering, operations research, applied mathematics, and related fields. Only an introductory background in operations research and supply chain management is assumed.

This book presents advanced mathematical programming models for contemporary supply chain risk optimization problems. It focuses on cutting‑edge issues such as supply chain viability under long‑term disruption risks, including reshoring decisions; optimization of digital supply chain cybersecurity and physical resilience in cyber‑physical supply chains; and supply chain fairness with respect to cost–service trade‑offs, profit distribution, and the allocation of cybersecurity investments. It also introduces computationally efficient decision‑making frameworks for emerging challenges in global supply chain management, including the reduction of cyber and physical risks and the enhancement of resilience and fairness. Each chapter ends with a table summarizing major managerial insights and the end-of-chapter problems to help the reader a self-check of material comprehension and to encourage for a further self-study. The book is intended for practitioners, researchers, and master’s and PhD‑level students in supply chain management, industrial engineering, operations research, applied mathematics, and related fields. Only an introductory background in operations research and supply chain management is assumed.

Viability, Cybersecurity, and Fairness

Optimization Models for Supply Chains

Chapman & Hall/CRC Texts in Statistical Science

From Alan Turing breaking the Enigma code to ChatGPT reshaping how we work and create, artificial intelligence has always been powered by a single unifying principle: learning from data under uncertainty. This book reveals the mathematical machinery behind modern AI, weaving together Bayesian probability, statistical learning, and deep neural networks into a coherent intellectual framework. Whether you seek to understand why large language models hallucinate, how recommendation systems predict your preferences, or what makes reinforcement learning agents master complex games, this book equips you with both the theoretical foundations and practical intuitions that define the modern AI playbook.Key Features:<ul> <li>Builds Bayesian reasoning from first principles through historical examples like submarine search and WWII code-breaking</li> <li>Bridges classical statistics and deep learning, connecting linear regression to transformers</li> <li>Covers the complete AI stack: probability, decision theory, Gaussian processes, neural networks, CNNs, NLP, and LLMs</li> <li>Emphasizes uncertainty quantification-building systems that know what they don't know</li> <li>Practical applications across finance, healthcare, operations, and autonomous systems</li> <li>Emerging topics: AI agents, RLHF, and retrieval-augmented generation</li> </ul>Written for graduate students, data scientists, and quantitatively-minded practitioners, this book assumes comfort with calculus and basic probability while building sophisticated intuitions progressively. Business analysts will appreciate the decision-theoretic framing; engineers will value the architectural insights; researchers will find rigorous foundations for further study. Whether used as a course textbook, professional reference, or intellectual companion for understanding the AI revolution transforming every industry, this book delivers the rare combination of mathematical depth and accessible exposition that makes complex ideas genuinely understandable.

Foundations of Data Science

Bayes, AI, and Deep Learning

Handbook of U.S. Labor Statistics

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

Employment, Hours, and Earnings

A special edition to the Handbook of U.S. Labor Statistics: Employment, Earnings, Prices, Productivity, and Other Labor Data, this reference is a consolidated wealth of employment information, providing monthly and annual data on hours worked and earnings made by industry, including figures and summary information spanning several years. These data are presented for states and the 75 largest metropolitan statistical areas (MSAs). This edition features: · Nearly 300 tables with data on employment for each state, the District of Columbia, and the nation's seventy-five largest MSAs · Detailed, non-seasonally adjusted industry data organized by month and year · Hours and earnings data for each state by industry · An introduction for each state and the District of Columbia that denotes salient data and noteworthy trends, including changes in population and the civilian labor force, industry increases and declines, employment and unemployment statistics, and a chart detailing employment percentages by industry · Ranking of the seventy-five largest MSAs, including census population estimates, unemployment rates, and the percent change in total nonfarm employment · Concise technical notes that explain pertinent facts about the data, including sources, definitions, and significant changes, with references for further guidance · A comprehensive appendix that details the geographical components of the seventy-five largest MSAs The employment, hours, and earnings data in this publication provide a detailed and timely picture of the fifty states, the District of Columbia, and the nation's seventy-five largest MSAs. These data can be used to analyze key factors affecting state and local economies and to compare national cyclical trends to local-level economic activity.

States and Areas

Employment, Hours, and Earnings 2026

Multi-Genre Creative Writing

A Writer's Craft

Springer Series in Healthcare Management and Innovation

This book explores how artificial intelligence can transform healthcare systems by advancing equitable access to care. Persistent global disparities, driven by geography, socioeconomic status, and cultural barriers, limit timely and effective treatment for many. AI-enabled tools such as virtual triage, predictive analytics, and language translation offer transformative solutions for underserved populations. The book examines decentralized platforms and telehealth, with a focus on their impact on rural, minority, and marginalized communities. Drawing on insights from experts in policy, operations, and technology, it integrates AI with healthcare optimization, workforce management, and value-based care. Case studies cover clinical decision support, robotic surgery, maternal and mental health, and patient engagement. The book also analyzes the policy and economic frameworks needed to sustain innovation. Ultimately, it presents a comprehensive roadmap for building inclusive, resilient, and technologically advanced healthcare systems.

Tackling the Iron Triangle

Healthcare Transformation with AI

Business Statistics of the United States

Business Statistics of the United States is a comprehensive and practical collection of data from as early as 1913 that reflects the nation's economic performance. It provides several years of annual, quarterly, and monthly data in industrial and demographic detail, including key indicators such as: gross domestic product, personal income, spending, saving, employment, unemployment, the capital stock, and more. Business Statistics of the United States is the best place to find historical perspectives on the U.S. economy. Of equal importance to the data are the introductory highlights, extensive notes, and figures for each chapter that help users to understand the data, use them appropriately, and, if desired, seek additional information from the source agencies. Business Statistics of the United States provides a rich and deep picture of the American economy and contains approximately 3,500 time series. The data are predominantly from federal government sources, including: ·Board of Governors of the Federal Reserve System ·Bureau of Economic Analysis ·Bureau of Labor Statistics ·Census Bureau ·Employment and Training Administration ·Energy Information Administration ·Federal Housing Finance Agency ·Department of the Treasury

Patterns of Economic Change

Business Statistics of the United States 2026

The 7th edition of Silent Selling: Strategic Visual Merchandising is a vital resource equipping students with a dynamic understanding of the fast-paced developments in retailing, including advancements in visual merchandising and the online environment. The seventh edition features more than 125 new color photographs and discusses, digital marketing, generative AI, and the neuroscience human behavior that go into creating a retail space. New box features include "Master Classes," such as L. Frank Baum's legacy in visual merchandising to the arts of collaboration and communication, which get students thinking about their own experiences and what inspiration can be drawn from it to create engaging visual merchandising environment. The author also brings industry experience through "Judy Bell's 3-Step Innovation Theory," and Bell's Color Coordination Model to inform students of approaches to solving common visual merchandising issues and provide real-world connections to the theory.New to this Edition -"Master Class" series and used to highlight visual merchandising history, communication and presentation techniques, and reflect on student's personal experiences with digital marketing -Explore important industry applications through in-text activities like "Judy Bell's 3-Step Innovation Theory" and interactive exercises designed to provide real-world connections -Updated topic coverage, reflecting growing interest and developments in neuroscience, generative AI, and digital marketing -Every chapter begins with an all-new Design Gallery featuring retailers' history and analysis of their creative blueprints -First edition to include videos with author's industry insights and expertiseSTUDIO -Study smarter with self-quizzes featuring scored results and personalized study tips -Review concepts with flashcards of terms and definitions -Go deeper with video tutorials Instructor Resources -Instructor's Guide with Test Bank provides suggestions for planning the course and using the text in the classroom -PowerPoint® presentations include images from the book and provide a framework for lecture and discussion

Strategic Visual Merchandising with STUDIO

Silent Selling

In a globalised marketplace, professional integrity requires more than just following a code of conduct; it requires a sophisticated understanding of how different cultures and philosophies define morality. This comprehensive exploration of business ethics shifts the focus from "what" people are doing to "why" it matters, using diverse theoretical perspectives to illuminate the ethical landscape of contemporary trade.
Key features of the second edition: 
<ul>
 <li>Comprehensive Theory: Dedicated chapters for a range of ethical frameworks, now updated to include additional non-Western and critical perspectives.&nbsp; </li>
 <li>Practical Application: In-depth analysis of contemporary case studies and real-life scenarios, including a broad range of topical issues.&nbsp; </li>
 <li>Critical Engagement: Features 'Pause for Reflection' boxes and discussion questions designed to challenge students and develop independent ethical judgment.&nbsp; </li>
 <li>Multimedia Learning: Integrated video activities from contemporary sources to engage students with complex ethical dilemmas. </li>
</ul>
 
Mick Fryer&nbsp;has taught business ethics at Loughborough, Aberystwyth and Cardiff Universities. He has also written course material for the Open University.

Ethics Theory and Business Practice

Financial Risk Analytics

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