'Stats to Go' is a user-friendly guide for hospitality, leisure and tourism students who need to learn statistics and statistical techniques. 'Stats to go' is an ideal companion to hospitality, leisure and tourism studies as the breadth of coverage supports all taught numerical aspects of these types of course. Examples from hospitality, leisure and tourism organizations: * licensed premises * fast food outlets * hotels * theme parks and their environments are used to illustrate key issues of the text. The area of quantitative methods is one which many students find unapproachable or daunting. With the use of a clear learning structure, and a user friendly, non-theoretical approach, Buglear has created a text which students and lecturers alike will find indispensable.

Japan will recover and its economic achievements will once again earn the world's admiration, with sustained annual growth of three percent, perhaps more, well within reach. This is the confident forecast that begins Japanese Phoenix: The Long Road to Economic Revival by the author of Japan: The System That Soured, which several years ago accurately predicted Japan's current travails at a time when others were prematurely pronouncing full recovery. Katz warns however that there is bad news to go with the good. So deep-seated are Japan's dysfunctions that, even if it did everything right today, it would take at least five years for truly vibrant growth to take hold. But Japan will not do everything right. Opposition to reform is deep-seated and a myriad of vested interests and millions of jobs are at stake. Still he notes, there is little doubt that reform will succeed. Japanese Phoenix tells the story of the struggle between the forces of reform and the forces of resistance. It dissects Prime Minister Koizumi's role in the process, and explains why Japan is in so much trouble and what needs to be done. It explore the debates among economists and gives a careful progress report on all the moves made so far in the name of reform - from greater direct foreign investment, to the financial "Big Bang", to ending one-party rule by the Liberal Democratic Party. Katz concludes that this is just the second round of a 15-round fight. Japan is a great nation currently trapped in obsolete institutions. As it has before, Japan will find a way to surmount its problems and regain its forward progress.

In this "important and comprehensive" guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

This practical guide shows researchers how to tap the Internet for statistics about companies, markets, and industries; how to organize and present statistics; and how to evaluate them for reliability.

Dive into the core of Go programming and cover advanced topics like generics, concurrency, web services, and cutting-edge testing techniques in this comprehensive fourth edition. Key Features Fully updated with coverage of web services, TCP/IP, REST APIs, Go Generics, and Fuzzy Testing Apply your new knowledge to real-world exercises, building high-performance servers and robust command-line utilities, to deepen your learning Gain clarity on what makes Go different, understand its nuances and features for smoother Go development Book DescriptionMastering Go, now in its fourth edition, remains the go-to resource for real-world Go development. This comprehensive guide delves into advanced Go concepts, including RESTful servers, and Go memory management. This edition brings new chapters on Go Generics and fuzzy Testing, and an enriched exploration of efficiency and performance. As you work your way through the chapters, you will gain confidence and a deep understanding of advanced Go topics, including concurrency and the operation of the Garbage Collector, using Go with Docker, writing powerful command-line utilities, working with JavaScript Object Notation (JSON) data, and interacting with databases. You will be engaged in real-world exercises, build network servers, and develop robust command-line utilities. With in-depth chapters on RESTful services, the WebSocket protocol, and Go internals, you are going to master Go's nuances, optimization, and observability. You will also elevate your skills in efficiency, performance, and advanced testing. With the help of Mastering Go, you will become an expert Go programmer by building Go systems and implementing advanced Go techniques in your projects.What you will learn Learn Go data types, error handling, constants, pointers, and array and slice manipulations through practical exercises Create generic functions, define data types, explore constraints, and grasp interfaces and reflections Grasp advanced concepts like packages, modules, functions, and database interaction Create concurrent RESTful servers, and build TCP/IP clients and servers Learn testing, profiling, and efficient coding for high-performance applications Develop an SQLite package, explore Docker integration, and embrace workspaces Who this book is for Mastering Go is written primarily for Go programmers who have some experience with the language and want to become expert practitioners. You will need to know the basics of computer programming before you get started with this book, but beyond that, anyone can sink their teeth into it.

Develop a deep understanding of Kubernetes and other orchestration systems by building your own with Go and the Docker API. Orchestration systems like Kubernetes can seem like a black box: you deploy to the cloud and it magically handles everything you need. That might seem perfect—until something goes wrong and you don’t know how to find and fix your problems. Build an Orchestrator in Go (From Scratch) reveals the inner workings of orchestration frameworks by guiding you through creating your own. In Build an Orchestrator in Go (From Scratch) you will learn how to: Identify the components that make up any orchestration system Schedule containers on to worker nodes Start and stop containers using the Docker API Manage a cluster of worker nodes using a simple API Work with algorithms pioneered by Google’s Borg Demystify orchestration systems like Kubernetes and Nomad Build an Orchestrator in Go (From Scratch) explains each stage of creating an orchestrator with diagrams, step-by-step instructions, and detailed Go code samples. Don’t worry if you’re not a Go expert. The book’s code is optimized for simplicity and readability, and its key concepts are easy to implement in any language. You’ll learn the foundational principles of these frameworks, and even how to manage your orchestrator with a command line interface. About the technology Orchestration frameworks like Kubernetes and Nomad radically simplify managing containerized applications. Building an orchestrator from the ground up gives you deep insight into deploying and scaling containers, clusters, pods, and other components of modern distributed systems. This book guides you step by step as you create your own orchestrator—from scratch. About the book Build an Orchestrator in Go (From Scratch) gives you an inside-out perspective on orchestration frameworks and the low-level operation of distributed containerized applications. It takes you on a fascinating journey building a simple-but-useful orchestrator using the Docker API and Go SDK. As you go, you’ll get a guru-level understanding of Kubernetes, along with a pattern you can follow when you need to create your own custom orchestration solutions. What's inside Schedule containers on worker nodes Start and stop containers using the Docker API Manage a cluster of worker nodes using a simple API Work with algorithms pioneered by Google’s Borg About the reader For software engineers, operations professionals, and SREs. This book’s simple Go code is accessible to all programmers. About the author Tim Boring has 20+ years of experience in software engineering. For most of that time he has worked with orchestration systems, including Borg, Kubernetes, and Nomad. Table of Contents PART 1 INTRODUCTION 1 What is an orchestrator? 2 From mental model to skeleton code 3 Hanging some flesh on the task skeleton PART 2 WORKER 4 Workers of the Cube, unite! 5 An API for the worker 6 Metrics PART 3 MANAGER 7 The manager enters the room 8 An API for the manager 9 What could possibly go wrong? PART 4 REFACTORINGS 10 Implementing a more sophisticated scheduler 11 Implementing persistent storage for tasks PART 5 CLI 12 Building a command-line interface 13 Now what?

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.