You will have numerous opportunities to practice statistical techniques through learning checks, examples, demonstrations, and problems. Exam preparation is made easy with a student companion website that provides tutorials, crossword puzzles, flashcards, learning objectives, and more!

    Polya, How to Solve It will show anyone in any field how to think straight. In lucid and appealing prose, Polya reveals how the mathematical method of demonstrating a proof or finding an unknown can be of help in attacking any problem that can be reasoned out--from building a bridge to winning a game of anagrams. Generations of readers have relished Polya's deft--indeed, brilliant--instructions on stripping away irrelevancies and going straight to the heart of the problem.

    The book begins with an introduction to the language of statistics and then covers descriptive statistics and inferential statistics. Throughout, the author offers readers:- Difficulty Rating Index for each chapter′s material- Tips for doing and thinking about a statistical technique- Top tens for everything from the best ways to create a graph to the most effective techniques for data collection- Steps that break techniques down into a clear sequence of procedures- SPSS tips for executing each major statistical technique- Practice exercises at the end of each chapter, followed by worked out solutions.The book concludes with a statistical software sampler and a description of the best Internet sites for statistical information and data resources. Readers also have access to a website for downloading data that they can use to practice additional exercises from the book. Students and researchers will appreciate the book′s unhurried pace and thorough, friendly presentation.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    What will it take to turn this opportunity into reality in every classroom, school, and district? Continuing its tradition of mathematics education leadership, NCTM has defined and described the principles and actions, including specific teaching practices, that are essential for a high-quality mathematics education for all students. Principles to Actions: Ensuring Mathematical Success for All offers guidance to teachers, specialists, coaches, administrators, policymakers, and parents: Builds on the Principles articulated in Principles and Standards for School Mathematics to present six updated Guiding Principles for School MathematicsSupports the first Guiding Principle, Teaching and Learning, with eight essential, research-based Mathematics Teaching PracticesDetails the five remaining Principles--the Essential Elements that support Teaching and Learning as embodied in the Mathematics Teaching PracticesIdentifies obstacles and unproductive and productive beliefs that all stakeholders must recognize, as well as the teacher and student actions that characterize effective teaching and learning aligned with the Mathematics Teaching PracticesWith Principles to Actions, NCTM takes the next step in shaping the development of high-quality standards throughout the United States, Canada, and worldwide.

    In addition to fine-tuning and streamlining the prose and the overall presentation, the authors have comprehensively updated the text and the applications to reflect recent economic developments and topics of current interest. Students in particular will find the Study Guide, with its practice questions, exercises, and problems, to be an excellent source of study support and extra review material. It is available in both a one- and a two-volume edition.

    What's new in the Second Edition? 1. Fully compliant with the latest version of SPSS version 12 2. More coverage of advanced statistics including completely new coverage of non-parametric statistics. The book is 50 per cent longer than the First Edition. 3. Each section of each chapter now has a notation - 1,2 or 3 - referring to the intended level of study. This helps students navigate their way through the book and makes it user-friendly for students of ALL levels. 4. Has a 'how to use this book' section at the start of the text. 5. Characters in each chapter have defined roles - summarizing key points, to pose questions etc 6. Each chapter now has several examples for students to work through. Answers provided on the enclosed CD-ROM

    Learn the Alphabet and pronunciation as well as useful phrases in 8 categories, such as greetings, travel and directions, making friends to business and emergencies. Download, read and enjoy your vacation like never before.

    Using real-life case studies and written with a student-centered approach, this new edition provides students with the necessary knowledge and skills to enable them to undertake a piece of business research making the best use of IT where appropriate.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    These areas of knowledge have converged into a modern theory of epidemiology that has been slow to penetrate into textbooks, particularly at the introductory level. Epidemiology: An Introduction closes the gap. It begins with a brief, lucid discussion of causal thinking and causal inference and then takes the reader through the elements of epidemiology, focusing on the measures of disease occurrence and causal effects. With these building blocks in place, the reader learns how to design, analyze and interpret problems that epidemiologists face, including confounding, the role of chance, and the exploration of interactions. All these topics are layered on the foundation of basic principles presented in simple language, with numerous examples and questions for further thought.

    It presents positioning and projection information in an easy-to-read, bulleted format on one side of the page spread, with corresponding positioning photos, radiographic images and anatomical drawings on the other side. Expert content covers pathology, geriatric and pediatric patient populations, survey information, and 100 new positioning photographs for the latest in radiographic positioning. The 6th edition contains a new chapter on digital imaging, and digital imaging information is incorporated where appropriate throughout the book. New photographs and redrawn illustrations create a consistent, visual appearance throughout the book.- Characterized by a clear, easy-to-follow organization that features one projection per page. Positioning and projection information is presented in an easy-to-read bulleted format on the left side of the page, and positioning photos, radiographic images and anatomical drawings are aligned on the right. This show and tell style helps students visualize anatomy and understand positioning.- Includes about 200 of the most commonly requested projections. Competency in performing these projections is necessary for all entry-level practitioners. By contrast, Merrill's Atlas includes over 400 projections and much more information on advanced imaging.- Critique Radiographs provide the basis of classroom or lab discussion. The WB/LM contains questions specific to these radiographs.- Pathologic Indications in appropriate chapters - Introducing pathology with positioning helps students understand the whole patient and improves their ability to produce radiographs that make diagnosis easy for the physician.- Pediatric Applications in appropriate chapters prepare technologists to deal competently with the special needs of their pediatric patients.- Geriatric Applications in appropriate chapters - Important information for technologists to understand the varying needs of their patient base.- Alternative Modalities or procedures inform students of which projections can better demonstrate certain anatomical parts or pathology, or which may be necessary if patient is unable to cooperate fully.- Radiographic Criteria on positioning pages help students develop a routine for evaluating radiographic quality.- Pathology Demonstrated provides students with a larger frame of reference, and therefore a greater understanding, of each projectionA new chapter on digital imaging discusses basic principles, applications, and image quality - digital imaging information essential for making appropriate positioning adjustments - to ensure readers are prepared to encounter new technology in clinical practice.Content updates include a totally new section on surgical radiography, new sections in all chapters on digital imaging considerations, an expanded section on bone densitometry, and a new introduction to positron emission tomography (PET).Updated and revised chapters cover angiography and interventional procedures, and computed tomography.More than 150 new positioning photos, in addition to many updated images, complement the new material.

    This completely revised edition of Enhancing Adult Motivation to Learn offers updated, culturally responsive practical advice and strategies in the jargon-free, readable style that made the original work so popular. This valuable resource is for teachers, trainers, and anyone who wants learning to be a motivating experience for all adults.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    Based on the popular blog, Smart Classroom Management, the book progresses step-by-step through 46 keys, showing you how to manage your classroom in a way that inspires your students to want to behave. By the end, you will have the knowledge to take over any K-8 classroom and create the kind of peaceful buy joyous learning experience your students will always remember.