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Larner S: Attacking the Space / LF

Attacking the Space

Inside Rugby's Tactical and Data Revolution - 'Illuminating' Eddie Jones

Offering a wide range of case studies, this new book highlights the practical applications of integrating quality management, data analysis, and multidisciplinary research for solving urgent environmental challenges, improving public health and company operations, and more. By bridging the gap between theory and practice, it emphasizes the transformative power of data and interdisciplinary approaches in addressing complex challenges and driving innovation.This book highlights many methods and applications for data analysis and interdisciplinary research, including various statistical methods, CUSUM (Cumulative Sum) control charts, Poisson distribution models, the Bayesian approach, software programs like Mathematica, machine learning algorithms, big data, and more. The book applies data analysis approaches in addressing complex challenges in many areas, including for environmental problems such as measuring air pollution; in socioeconomic issues like insurance costs and dynamics; in healthcare such as for analyzing epidemiological data (such as from the COVID-19 pandemic); in the agricultural sector, such as to understand and forecast agricultural trends and to enhance agricultural sustainability; and more.

Integrative Approaches to Quality, Data Analysis, and Interdisciplinary Research

International Series on Actuarial Science

This comprehensive yet accessible guide to enterprise risk management for financial institutions contains all the tools needed to build and maintain an ERM framework. It discusses the internal and external contexts within which risk management must be carried out, and it covers a range of qualitative and quantitative techniques that can be used to identify, model and measure risks. This third edition has been thoroughly revised and updated to reflect new regulations and legislation. It includes additional detail on machine learning, a new section on vine copulas, and significantly expanded information on sustainability. A range of new case studies include Theranos and FTX. Suitable as a course book or for self-study, this book forms part of the core reading for the Institute and Faculty of Actuaries' examination in enterprise risk management.

Financial Enterprise Risk Management

Understand how to use people analytics to drive business results and gain competitive advantage.

Using HR Data and AI to Drive Business Results

The Value of People Analytics

Implement AI strategies to optimise performance and deliver stronger customer experiences in tourism.

Technology-Led Tourism is a practical guide for managers, department heads and industry professionals who want to develop credible strategies for applying AI across the travel sector. It bridges the gap between technology and tourism, offering frameworks you can implement to enhance both operational efficiency and guest engagement.

Written by Shaon Talukder, this book draws on detailed real-world examples from Expedia, Amadeus, Delta Airlines and Airbnb to show how AI principles are already reshaping travel. With insights from adjacent industries such as finance and media, it highlights proven approaches that tourism professionals can adapt to stay competitive. 

You'll learn how to:
- Apply AI frameworks to optimize operations and decision-making 
- Develop data foundations that enable scalable, reliable innovation 
- Implement principles from other industries to strengthen strategy 
- Build credibility by applying actionable tools to your own context 
- Translate AI opportunities into measurable career and business impact 

With clear models, real-world examples, and actionable guidance, Technology-Led Tourism equips mid- to senior-career professionals to implement strategies that not only improve performance but also elevate their role as informed, forward-looking leaders in the industry.

Themes include: AI in tourism, travel strategy, data frameworks, operational efficiency, customer experience, innovation adoption

Leveraging AI, Data and Analytics in Travel

Technology-Led Tourism

Use this jargon-free, step-by-step guide to create an agile, customer-centric marketing strategy and unlock the full capability of data and analytics.

Leverage Analytics, Data and AI to Optimize Marketing Strategies

Marketing Metrics

County and City Extra Series

The Who, What, and Where of America is designed to provide a sampling of key demographic information. It covers the United States, every state, each metropolitan statistical area, and all the counties and cities with a population of 20,000 or more. 

Who: Age, Race and Ethnicity, and Household Structure
What: Education, Employment, and Income
Where: Migration, Housing, and Transportation

Each part is preceded by highlights and ranking tables that show how areas diverge from the national norm. These research aids are invaluable for understanding data from the ACS and for highlighting what it tells us about who we are, what we do, and where we live.

Each topic is divided into four tables revealing the results of the data collected from different types of geographic areas in the United States, generally with populations greater than 20,000. 
·Table A. States
·Table B. Counties
·Table C. Metropolitan Areas
·Table D. Cities

In this edition, you will find social and economic estimates on the ways American communities are changing with regard to the following:
·Age and race
·Health care coverage
·Marital history
·Education attainment
·Income and occupation
·Commute time to work
·Employment status
·Home values and monthly costs
·Veteran status
·Size of home or rental unit

This title is the latest in the County and City Extra Series of publications from Bernan Press. Other titles include County and City Extra, County and City Extra: Special Decennial Census Edition, and Places, Towns, and Townships.

Understanding the American Community Survey

The Who, What, and Where of America

Develop a marketing strategy that blends data-driven principles with authentic human insight to deliver stronger, more meaningful results.

Authentic Marketing is a practical guide for mid-career marketers who want to build credibility, apply clear frameworks and develop campaigns that stand out in an increasingly AI-driven landscape. As conversations about automation dominate the industry, this book reframes what truly drives marketing effectiveness: human curiosity, creativity and audience-first thinking.

Written by industry leader Visha Kudhail, the book provides actionable tools for integrating authentic inspiration with data-driven approaches. Through detailed chapters and real-world examples, it shows how to implement strategies that optimize performance, build trust and strengthen long-term consumer loyalty.

You'll learn how to:
- Apply audience-first principles to develop creative ideas grounded in real human insight
- Implement data-driven strategies that support authenticity rather than replace it
- Develop frameworks for balancing automation with the emotional intelligence marketing requires
- Optimize campaigns by identifying meaningful audience motivations and behaviours
- Use real-world examples to strengthen credibility and apply best practices across industries

With its balance of strategy, practical guidance and modern industry insight, Authentic Marketing helps mid-career professionals develop campaigns that deliver measurable impact while staying true to the human foundations of great marketing.

Themes include: marketing strategy, creativity frameworks, audience insight, authentic storytelling, data-driven marketing, campaign optimization

Combining Human Thinking and Creativity with Technology to Inspire Audiences

Authentic Marketing

This publication addresses copula approaches to competing risks models for dependent latent failure times. It will establish the fundamentals on dependent competing risks models, as well as a range of recent developments to identifiability and estimation using copulas. Readers will learn from the presentation of theory, in relation to its applications in different subject areas in economics, engineering, and medicine. The comprehensive knowledge provided in this book gives readers an overview of existing models for dependent competing risks, which are not found in other books.The book covers basic statistical ideas, such as "parametric latent failure time models", theoretical issues, such as "identifiability of the competing risks model", and model comparisons, such as comparative studies for "different copulas and different models for hazard functions". Aside from the introductory materials, the authors cover new and recently developed methodologies. The new solutions address the identifiability problems in competing risks models that rely on copula modelling. Copula models and other competing risks models are presented in unified theoretical framework and illustrated with data from various disciplines (such as economics, engineering, and medicine). The book also includes applications with real data and the code (written by R and/or Stata) will be made available for easy practice purposes.A selection of exercises and their solutions will be available online. This book serves as a good reading for senior undergraduates and postgraduate students studying in such courses as "Multivariate Survival Analysis", "Survival Data Analysis" or "Advanced Econometrics". This book would also serve as a useful reference for empirical researchers in a wide range of disciplines.

Theory and Applications in Economics, Engineering, Medicine

Copula Models for Dependent Competing Risks

Conventional "frequentist" methods that dominate the field of statistics are generally inconsistent and liable to catastrophic failure in some contexts. These weaknesses have become particularly concerning in relation to crises of replicability and credibility in science. Two alternatives have been proposed to address these flaws--classical Bayesian inference and the principle of maximum entropy--but the connections between them remain controversial. Making Statistics Work presents a synthesis of information theory and Bayesian inference that addresses these fundamental problems. It provides a consistent, powerful, and flexible framework for data inference based on rigorous logic derived from first principles, allowing for new approaches to many of the unresolved questions of statistics. Duncan K. Foley and Ellis Scharfenaker illustrate the application of this framework and the reasoning behind it across a variety of important statistical problems, such as the inference underlying "gold standard" clinical trials, models of human behavior employed in behavioral finance and psychology, analysis of macroeconomic policy, the relationship of classical probability to quantum physics, and the limitations of linear regression analysis. Making Statistics Work offers new insight into contentious topics, from problems of causality and confounding variables in randomized experimental trials to the foundations of Bayesian and frequentist probability theory.

Information Theory and Bayesian Inference

Making Statistics Work

Elements in Econophysics

Classical mechanics provided the conceptual and methodological foundations of neoclassical economics, which has its roots in economic individualism. Since the early twentieth century, statistical mechanics has underpinned a lesser-known approach to economics and finance, one that focuses on aggregates and the interactions between individuals. This has led to the emergence of a new field of research, known as econophysics, which brings to the fore concepts such as emergent properties, power laws, networks, entropy, and multifractality, thereby reshaping economic enquiry.

A Connected History of Two Disciplines

The Rise of Econophysics

Attacking the Space

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