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Larner S: Attacking the Space / LF

Attacking the Space

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

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

Statistical skills are essential for analysing data and ensuring optimal business operation and efficiency. In this clear and concise textbook, Les Oakshott and Kathy Kotiadis guide students through key quantitative techniques, from basic maths and statistics through to advanced topics such as hypothesis testing and linear programming. Grounded in the everyday realities of business, this textbook introduces each chapter with an engaging case study to highlight how organisations operationalise these techniques, ranging from the growth of China's economy and a Covid-19 infection survey to goal scoring at Euro 2024 and the effect of global warming on the occurrence of salmonella in Singapore. New to this edition: -Links the UN Sustainable Development Goals to quantitative techniques -Greater emphasis on Excel to enable seamless transition to blended learning approaches -Walk-through videos of key processes hosted on the companion website This is the essential textbook for delivering quantitative methods and business statistics modules to students of mixed maths abilities across undergraduate and postgraduate levels. Accompanying online resources for this title can be found at bloomsburypub/essential-quantitative-methods-8e. These resources are designed to support teaching and learning at no extra cost.

for Business, Management and Finance

Essential Quantitative Methods

The back-to-back Rugby World Cup-winning Springbok team has captured the imagination of South Africans in a way that has never been achieved before. This team serves as a fascinating case study of what is possible when an organisation focuses on being not just smart, but also healthy. By incorporating and modelling specific principles that aim to enhance the experience of players, staff and coaches, the team has managed to become more than the sum of its parts. This book unpacks these principles in a way that equips anyone responsible for leading a group, team or organisation with the tools to replicate what the Boks have managed to achieve in their own context. By drawing on personal and media interviews with those who helped shape their environment, including Jacques Nienaber and Steven Kitshoff, the book provides practical examples that will enable the reader with the know-how to do it themselves. The Bok Way is for anyone who wants to build a great team of their own and needs some stepping stones on the way. The principles highlighted are taken from the best-practice knowledge of organisational health and employee experience and is packaged in such a way to make it relevant, practical and entertaining.

Unlocking the Springboks' Secrets to Performance, Culture and Success in Business

The BOK Way

Learn essential strategies to streamline and secure your organization's data handling from a cybersecurity expert who has trained military intelligence personnel. When a cyber security incident occurs, how does anyone know? Data must leave workstations and servers, bounce across the network, and land in a central database before analysts can use it. This project-based book covers that complex space between an organization’s computers and the security analyst tasked with protecting them. The guidance is straightforward, and the focus is on streamlining the process of gathering, transforming, and storing cybersecurity data using free and open-source tools. The author elaborates on core logging strategies, while also emphasizing the importance of standardizing data, using encryption to protect transmitted data, and creating “data pipelines” that support cybersecurity, data analytics, and automation needs alike. You’ll how to: <ul><li>Implement core logging strategies using free tools such as the Elastic stack</li><li>Transform data to fit your needs, and configure your tools to send it back and forth&nbsp;</li><li>Secure your logging infrastructure by encrypting connections using TLS and SSH&nbsp;</li><li>Handle version control and backups with Git, and improve your efficiency with caching</li></ul> By the end, you’ll know how to enrich your security data, protect it from unauthorized parties, and automate your workflow in the process – leaving more room for creative thinking.

Learn essential strategies to streamline and secure your organization's data handling from a cybersecurity expert who has trained military intelligence personnel. When a cyber security incident occurs, how does anyone know? Data must leave workstations and servers, bounce across the network, and land in a central database before analysts can use it. This project-based book covers that complex space between an organization’s computers and the security analyst tasked with protecting them. The guidance is straightforward, and the focus is on streamlining the process of gathering, transforming, and storing cybersecurity data using free and open-source tools. The author elaborates on core logging strategies, while also emphasizing the importance of standardizing data, using encryption to protect transmitted data, and creating “data pipelines” that support cybersecurity, data analytics, and automation needs alike. You’ll how to: <ul><li>Implement core logging strategies using free tools such as the Elastic stack</li><li>Transform data to fit your needs, and configure your tools to send it back and forth&nbsp;</li><li>Secure your logging infrastructure by encrypting connections using TLS and SSH&nbsp;</li><li>Handle version control and backups with Git, and improve your efficiency with caching</li></ul> By the end, you’ll know how to enrich your security data, protect it from unauthorized parties, and automate your workflow in the process – leaving more room for creative thinking.

Build Secure Data Pipelines with Free and Open-Source Tools

Data Engineering for Cybersecurity

Develop analytical skills that are in high demand with Camm/Cochran/Fry/Ohlmann's "Business Analytics," 6th Edition. Master the full range of analytics as you strengthen descriptive, predictive and prescriptive analytic skills, data visualization, unsupervised and supervised machine learning and generative AI. Examples and visuals illustrate data and results. Step-by-step instructions guide you through using Excel, Tableau, R, Power BI or Python (including the Python-based Orange software). Practical problems at all levels of difficulty let you apply what you've learned. Updates address topics beyond traditional quantitative concepts such as data wrangling, data visualization, machine learning and generative AI. MindTap and WebAssign online learning platforms are available with an interactive eBook, algorithmic practice problems and Exploring Analytics visualizations.

Business Analytics

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

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

Discover the AI and data skills you'll need and develop your confidence to succeed in the digital age.

Gain the Confidence You Need to Succeed

Data and AI Skills

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

Probability and Statistics for Engineering and the Sciences, Loose-Leaf Version

Performance Attribution Volume 2: Analysis and Reporting, Second Edition explains the practical aspects of building or interpreting a top-to-bottom performance attribution system applicable to many asset classes. Requiring a familiarity with the principal concepts of portfolio analysis, it features standard methodologies and alternative approaches to the attribution of diverse assets, including derivatives, fixed income, and hedge funds. Based on the authors' Performance Evaluation and Attribution of Security Portfolios (2012), its concentration on the ethical standards embodied by GIPS includes a summary of provisions for the presentation of risk in a firm's investments.

Analysis and Reporting

Performance Attribution Volume Two

Attacking the Space

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