It helps in the process of choosing the right statistical technique and includes a detailed guide to interpreting SPSS ouput.

    The text is supported by a number of features to enhance student understanding as well as supplements to consolidate the learning process.

    Find out how the Swedish police combined XP, Scrum, and Kanban in a 60-person project. From start to finish, you'll see how to deliver a successful product using Lean principles. We start with an organization in desperate need of a new way of doing things and finish with a group of sixty, all working in sync to develop a scalable, complex system. You'll walk through the project step by step, from customer engagement, to the daily "cocktail party," version control, bug tracking, and release. In this honest look at what works--and what doesn't--you'll find out how to: Make quality everyone's business, not just the testers. Keep everyone moving in the same direction without micromanagement. Use simple and powerful metrics to aid in planning and process improvement. Balance between low-level feature focus and high-level system focus. You'll be ready to jump into the trenches and streamline your own development process.ContentsForewordPrefacePART I: HOW WE WORK1. About the Project1.1 Timeline 51.2 How We Sliced the Elephant 61.3 How We Involved the Customer 72. Structuring the Teams3. Attending the Daily Cocktail Party3.1 First Tier: Feature Team Daily Stand-up3.2 Second Tier: Sync Meetings per Specialty3.3 Third Tier: Project Sync Meeting4. The Project Board4.1 Our Cadences4.2 How We Handle Urgent Issues and Impediments5. Scaling the Kanban Boards6. Tracking the High-Level Goal7. Defining Ready and Done7.1 Ready for Development7.2 Ready for System Test7.3 How This Improved Collaboration 8. Handling Tech Stories8.1 Example 1: System Test Bottleneck8.2 Example 2: Day Before the Release8.3 Example 3: The 7-Meter Class9. Handling Bugs9.1 Continuous System Test9.2 Fix the Bugs Immediately9.3 Why We Limit the Number of Bugs in the Bug Tracker9.4 Visualizing Bugs9.5 Preventing Recurring Bugs10. Continuously Improving the Process10.1 Team Retrospectives10.2 Process Improvement Workshops10.3 Managing the Rate of Change11. Managing Work in Progress11.1 Using WIP Limits11.2 Why WIP Limits Apply Only to Features12. Capturing and Using Process Metrics12.1 Velocity (Features per Week)12.2 Why We Don’t Use Story Points12.3 Cycle Time (Weeks per Feature)12.4 Cumulative Flow12.5 Process Cycle Efficiency13. Planning the Sprint and Release13.1 Backlog Grooming13.2 Selecting the Top Ten Features13.3 Why We Moved Backlog Grooming Out of the Sprint Planning Meeting13.4 Planning the Release14. How We Do Version Control14.1 No Junk on the Trunk14.2 Team Branches14.3 System Test Branch15. Why We Use Only Physical Kanban Boards16. What We Learned16.1 Know Your Goal16.2 Experiment16.3 Embrace Failure16.4 Solve Real Problems16.5 Have Dedicated Change Agents16.6 Involve PeoplePART II: A CLOSER LOOK AT THE TECHNIQUES 17. Agile and Lean in a Nutshell17.1 Agile in a Nutshell17.2 Lean in a Nutshell17.3 Scrum in a Nutshell17.4 XP in a Nutshell17.5 Kanban in a Nutshell18. Reducing the Test Automation Backlog18.1 What to Do About It18.2 How to Improve Test Coverage a Little Bit Each Iteration18.3 Step 1: List Your Test Cases18.4 Step 2: Classify Each Test18.5 Step 3: Sort the List in Priority Order18.6 Step 4: Automate a Few Tests Each Iteration18.7 Does This Solve the Problem?19. Sizing the Backlog with Planning Poker19.1 Estimating Without Planning Poker19.2 Estimating with Planning Poker19.3 Special Cards20. Cause-Effect Diagrams20.1 Solve Problems, Not Symptoms20.2 The Lean Problem-Solving Approach: A3 Thinking20.3 How to Use Cause-Effect Diagrams20.4 Example 1: Long Release Cycle20.5 Example 2: Defects Released to Production20.6 Example 3: Lack of Pair Programming20.7 Example 4: Lots of Problems20.8 Practical Issues: How to Create and Maintain the Diagrams20.9 Pitfalls20.10 Why Use Cause-Effect Diagrams?21. Final WordsA1. Glossary: How We Avoid Buzzword BingoIndex

    All I Need to Know About Manufacturing I Learned in Joe's Garage: World Class Manufacturing Made Simple

    It is more than a book about brands, and contains many sound lessons for strategy and the role of leaders.­­Michael E. Porter, Harvard Business SchoolPractical, psychologically astute, and clearly written, this book has much to offer business folk of all stripes.­­Publishers Weekly

    Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." --Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching"This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." --Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education"Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." --Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching"As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." --From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

    Previously undocumented, these 23 patterns allow designers to create more flexible, elegant, and ultimately reusable designs without having to rediscover the design solutions themselves.The authors begin by describing what patterns are and how they can help you design object-oriented software. They then go on to systematically name, explain, evaluate, and catalog recurring designs in object-oriented systems. With Design Patterns as your guide, you will learn how these important patterns fit into the software development process, and how you can leverage them to solve your own design problems most efficiently. Each pattern describes the circumstances in which it is applicable, when it can be applied in view of other design constraints, and the consequences and trade-offs of using the pattern within a larger design. All patterns are compiled from real systems and are based on real-world examples. Each pattern also includes code that demonstrates how it may be implemented in object-oriented programming languages like C++ or Smalltalk.

    The material is reinforced with numerous examples to illustrate principles and imaginative, well-illustrated problems of varying degrees of difficulty. The book is committed to developing users' problem-solving skills. Features new "Photorealistc" figures (approximately 400) that have been rendered in often 3D photo quality detail to appeal to visual learners. Presents a thorough combination of both static and dynamic engineering mechanics theory and applications. Features a large variety of problem types from a broad range of engineering disciplines, stressing practical, realistic situations encountered in professional practice, varying levels of difficulty, and problems that involve solution by computer. For professionals in mechanical engineering, civil engineering, aeronautical engineering, and engineering mechanics careers.

    But for some reason they choose to ignore those guidelines and churn out turgid, pompous, and obscure prose. Distinguished sociologist Howard S. Becker, true to his calling, looks for an explanation for this bizarre behavior not in the psyches of his colleagues but in the structure of his profession. In this highly personal and inspirational volume he considers academic writing as a social activity.Both the means and the reasons for writing a thesis or article or book are socially structured by the organization of graduate study, the requirements for publication, and the conditions for promotion, and the pressures arising from these situations create the writing style so often lampooned and lamented. Drawing on his thirty-five years' experience as a researcher, writer, and teacher, Becker exposes the foibles of the academic profession to the light of sociological analysis and gentle humor. He also offers eminently useful suggestions for ways to make social scientists better and more productive writers. Among the topics discussed are how to overcome the paralyzing fears of chaos and ridicule that lead to writer's block; how to rewrite and revise, again and again; how to adopt a persona compatible with lucid prose; how to deal with that academic bugaboo, "the literature." There is also a chapter by Pamela Richards on the personal and professional risks involved in scholarly writing.In recounting his own trials and errors Becker offers his readers not a model to be slavishly imitated but an example to inspire. Throughout, his focus is on the elusive work habits that contribute to good writing, not the more easily learned rules of grammar and punctuation. Although his examples are drawn from sociological literature, his conclusions apply to all fields of social science, and indeed to all areas of scholarly endeavor. The message is clear: you don't have to write like a social scientist to be one.

    Emphasis is placed upon the theoretical basis of each type of instrument, its optimal area of application, its sensitivity, its precision, and its limitations. The text also introduces students to elementary integrated circuitry, microprocessors and computers, and treatment of analytical data.

    Through text, case studies, and hands-on exercises, the book guides students in discovering the concepts of entrepreneurship and the competencies, skills, know-how and experience that are sufficient to pursue different entrepreneurial opportunities. The authors recognize that there is no substitute for actually startinga company, but believe that it is possible to expose students to many of the vital issues and immerse them in key learning experiences.

    This new edition includes the latest research and case studies, and offers inspiring new and relevant stories of real people achieving extraordinary results.

    Because the information in the unconscious is in an unruly and often disturbing form, a "censor" in the preconscious will not allow it to pass unaltered into the conscious. During dreams, the preconscious is more lax in this duty than in waking hours, but is still attentive: as such, the unconscious must distort and warp the meaning of its information to make it through the censorship. As such, images in dreams are often not what they appear to be, according to Freud, and need deeper interpretation if they are to inform on the structures of the unconscious.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    Amazing new tools, materials and skills turn us all into makers. Using technology to make, repair or customize the things we need brings engineering, design and computer science to the masses. Fortunately for educators, this maker movement overlaps with the natural inclinations of children and the power of learning by doing. The active learner is at the center of the learning process, amplifying the best traditions of progressive education. This book helps educators bring the exciting opportunities of the maker movement to every classroom. Children are natural tinkerersTheir seminal learning experiences come through direct experience with materials. Digital fabrication, such as 3D printing and physical computing, including Arduino, MaKey MaKey and Raspberry Pi, expands a child’s toy and toolboxes with new ways to make things and new things to make. For the first time ever, childhood inventions may be printed, programmed or imbued with interactivity. Recycled materials can be brought back to life. While school traditionally separates art and science, theory and practice, such divisions are artificial. The real world just doesn’t work that way! Architects are artists. Craftsmen deal in aesthetics, tradition and mathematical precision. Video game developers rely on computer science. Engineering and industrial design are inseparable. The finest scientists are often accomplished musicians. The maker community brings children, hobbyists and professionals together in a glorious celebration of personal expression with a modern flare. When 3-D printing, precision cutting, microcomputer control, robotics and computer programming become integral to the art studio, auto shop or physics lab, every student needs access to tools, knowledge and problem solving skills. The maker movement not only blurs the artificial boundaries between subject areas, it erases distinctions between art and science while most importantly obliterating the crippling practice of tracking students in academic pursuits or vocational training. There are now multiple pathways to learning what we have always taught and things to do that were unimaginable just a few years ago. Making for every classroom budgetEven if you don’t have access to expensive (but increasingly affordable) hardware, every classroom can become a makerspace where kids and teachers learn together through direct experience with an assortment of high and low-tech materials. The potential range, breadth, power, complexity and beauty of projects has never been greater thanks to the amazing new tools, materials, ingenuity and playfulness you will encounter in this book. In this practical guide, Sylvia Martinez and Gary Stager provide K-12 educators with the how, why, and cool stuff that supports classroom making.