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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. NOTE: You are purchasing a standalone product; MyStatLab does not come packaged with this content. If you would like to purchase both the physical text and MyStatLab search for: 0133956490 / 9780133956498 Stats: Data and Models Plus NEW MyStatLab with Pearson eText -- Access Card Package Package consists of: 0321847997 / 9780321847997 My StatLab Glue-in Access Card 032184839X / 9780321848390 MyStatLab Inside Sticker for Glue-In Packages 0321986490 / 9780321986498 Stats: Data and Models MyStatLab should only be purchased when required by an instructor. For one-or-two semester introductory statistics courses. Richard De Veaux, Paul Velleman, and David Bock wrote Stats: Data and Models with the goal that students and instructors have as much fun reading it as they did writing it. Maintaining a conversational, humorous, and informal writing style, this new edition engages students from the first page. The authors focus on statistical thinking throughout the text and rely on technology for calculations. As a result, students can focus on developing their conceptual understanding. Innovative Think/Show/Tell examples give students a problem-solving framework and, more importantly, a way to think through any statistics problem and present their results. The Fourth Edition is updated with instructor podcasts, video lectures, and new examples to keep material fresh, current, and relevant to today’s students.
Revised edition of the authors' Business statistics, [2015]
NOTE: Before purchasing, check with your instructor to ensure you select the correct ISBN. Several versions of the MyLab(tm) and Mastering(tm) platforms exist for each title, and registrations are not transferable. To register for and use MyLab or Mastering, you may also need a Course ID, which your instructor will provide. Used books, rentals, and purchases made outside of Pearson If purchasing or renting from companies other than Pearson, the access codes for the MyLab platform may not be included, may be incorrect, or may be previously redeemed. Check with the seller before completing your purchase. For two-semester business statistics courses. This package includes MyLab Business Statistics. Relevant statistical methods that empower individuals to make effective, data-informed business decisions Business Statistics, 4th Edition , by Sharpe, De Veaux, and Velleman, narrows the gap between theory and practice, by covering relevant and real-life statistical methods that help business students make good, data-driven decisions. With their unique blend of teaching, consulting, and entrepreneurial experiences, this dynamic author team brings a modern edge to teaching statistics to business students. Focusing on stats in the context of real business issues, with an emphasis on analysis and understanding over computation, the text helps students to be analytical, prepares them to make better business decisions, and shows them how to effectively communicate results. Personalize learning with MyLab Business Statistics MyLab(tm) is the teaching and learning platform that empowers you to reach every student. By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student. 0134684877 / 9780134684871 Business Statistics Plus MyLab Statistics with Pearson eText -- Access Card Package, 4/e Package consists of: 0134705211 / 9780134705217 Business Statistics 0134783034 / 9780134783031 MyLab Statistics with Pearson eText -- Standalone Access Card -- for Business Statistics
Discover how to build your own smart Internet of Things projects and bring a new degree of interconnectivity to your world About This Book Learn how to extract and analyse data from physical devices and build smart IoT projects Master the skills of building enticing projects such as a neural network autonomous car, computer vision through a camera, and cloud-based IoT applications This project-based guide leverages revolutionary computing chips such as Raspberry Pi, Arduino, and so on Who This Book Is For If you are hobbyist who is keen on making smart IoT projects, then this book is for you. You should have a basic knowledge of Python. What You Will Learn Implement data science in your IoT projects and build a smart temperature controller Create a simple machine learning application and implement decision system concepts Develop a vision machine using OpenCV Build a robot car with manual and automatic control Implement speech modules with your own voice commands for IoT projects Connect IoT to a cloud-based server In Detail Internet of Things (IoT) is a groundbreaking technology that involves connecting numerous physical devices to the Internet and controlling them. Creating basic IoT projects is common, but imagine building smart IoT projects that can extract data from physical devices, thereby making decisions by themselves. Our book overcomes the challenge of analyzing data from physical devices and accomplishes all that your imagination can dream up by teaching you how to build smart IoT projects. Basic statistics and various applied algorithms in data science and machine learning are introduced to accelerate your knowledge of how to integrate a decision system into a physical device. This book contains IoT projects such as building a smart temperature controller, creating your own vision machine project, building an autonomous mobile robot car, controlling IoT projects through voice commands, building IoT applications utilizing cloud technology and data science, and many more. We will also leverage a small yet powerful IoT chip, Raspberry Pi with Arduino, in order to integrate a smart decision-making system in the IoT projects. Style and approach The book follows a project-based approach to building smart IoT projects using powerful boards such as the Raspberry Pi, Arduino, and the IoT chip.
Roxy Peck, Chris Olsen and Jay Devore’s new edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. The Third Edition includes coverage of the graphing calculator and includes expanded coverage of probability. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. It helps students grasp concepts and cement their comprehension by using simple notation-frequently substituting words for symbols. Hands-on activities and interactive applets allow students to practice statistics firsthand. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
New to This Edition *Extensively revised to cover important new topics: Pearl' s graphing theory and SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. *Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. *Expanded coverage of psychometrics. *Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). *Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models. Pedagogical Features *Exercises with answers, plus end-of-chapter annotated lists of further reading. *Real examplesof troublesome data, demonstrating how to handle typical problems in analyses.
This clear and comprehensive guide provides everything you need for powerful linear model analysis. Using a tutorial approach and plenty of examples, authors Ramon Littell, Walter Stroup, and Rudolf Freund lead you through methods related to analysis of variance with fixed and random effects. You will learn to use the appropriate SAS procedure for most experiment designs (including completely random, randomized blocks, and split plot) as well as factorial treatment designs and repeated measures. SAS for Linear Models, Fourth Edition, also includes analysis of covariance, multivariate linear models, and generalized linear models for non-normal data. Find inside: regression models; balanced ANOVA with both fixed- and random-effects models; unbalanced data with both fixed- and random-effects models; covariance models; generalized linear models; multivariate models; and repeated measures. New in this edition: MIXED and GENMOD procedures, updated examples, new software-related features, and other new material. This book is part of the SAS Press program.

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