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Summarizing Data
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Book Synopsis Small Summaries for Big Data by : Graham Cormode
Download or read book Small Summaries for Big Data written by Graham Cormode and published by Cambridge University Press. This book was released on 2020-11-12 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to flexible, efficient tools for describing massive data sets to improve the scalability of data analysis.
Book Synopsis Amazing Animals: Working Dogs: Summarizing Data ebook by : Lisa MacDonald
Download or read book Amazing Animals: Working Dogs: Summarizing Data ebook written by Lisa MacDonald and published by Teacher Created Materials. This book was released on 2019-06-28 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day, heroes around the world go to work, help people, and keep them safe. And they do it all while wagging their tails! Working dogs can be found at hospitals, airports, schools, courtrooms, and in the military. Compare the important duties that service dogs, therapy dogs, screening dogs, guide dogs, and military working dogs perform and learn to summarize data. Packed with factual information and high-interest content, this fiction math book uses real-world examples of problem solving to build students' math and reading skills. Let's Explore Math sidebars feature math questions that challenge students to develop their math skills. A problem-solving section at the end of the book prompts students to reflect and apply what they've learned. Demystify math with this leveled book that makes learning math fun and accessible for kids ages 10-12 and appeals to reluctant readers.
Book Synopsis Amazing Animals: Working Dogs: Summarizing Data by : Lisa MacDonald
Download or read book Amazing Animals: Working Dogs: Summarizing Data written by Lisa MacDonald and published by Teacher Created Materials. This book was released on 2019-06-28 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every day, heroes around the world go to work, help people, and keep them safe. And they do it all while wagging their tails! Working dogs can be found at hospitals, airports, schools, courtrooms, and in the military. Compare the important duties that service dogs, therapy dogs, screening dogs, guide dogs, and military working dogs perform and learn to summarize data. Packed with factual information and high-interest content, this fiction math book uses real-world examples of problem solving to build students' math and reading skills. Let's Explore Math sidebars feature math questions that challenge students to develop their math skills. A problem-solving section at the end of the book prompts students to reflect and apply what they've learned. Demystify math with this leveled book that makes learning math fun and accessible for kids ages 10-12 and appeals to reluctant readers.
Book Synopsis Core Concepts in Data Analysis: Summarization, Correlation and Visualization by : Boris Mirkin
Download or read book Core Concepts in Data Analysis: Summarization, Correlation and Visualization written by Boris Mirkin and published by Springer Science & Business Media. This book was released on 2011-04-05 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Core Concepts in Data Analysis: Summarization, Correlation and Visualization provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate different aspects of data (decision trees, linear rules, neuron networks, and Bayes rule). Boris Mirkin takes an unconventional approach and introduces the concept of multivariate data summarization as a counterpart to conventional machine learning prediction schemes, utilizing techniques from statistics, data analysis, data mining, machine learning, computational intelligence, and information retrieval. Innovations following from his in-depth analysis of the models underlying summarization techniques are introduced, and applied to challenging issues such as the number of clusters, mixed scale data standardization, interpretation of the solutions, as well as relations between seemingly unrelated concepts: goodness-of-fit functions for classification trees and data standardization, spectral clustering and additive clustering, correlation and visualization of contingency data. The mathematical detail is encapsulated in the so-called “formulation” parts, whereas most material is delivered through “presentation” parts that explain the methods by applying them to small real-world data sets; concise “computation” parts inform of the algorithmic and coding issues. Four layers of active learning and self-study exercises are provided: worked examples, case studies, projects and questions.
Download or read book Data Science written by Field Cady and published by John Wiley & Sons. This book was released on 2020-12-30 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tap into the power of data science with this comprehensive resource for non-technical professionals Data Science: The Executive Summary – A Technical Book for Non-Technical Professionals is a comprehensive resource for people in non-engineer roles who want to fully understand data science and analytics concepts. Accomplished data scientist and author Field Cady describes both the “business side” of data science, including what problems it solves and how it fits into an organization, and the technical side, including analytical techniques and key technologies. Data Science: The Executive Summary covers topics like: Assessing whether your organization needs data scientists, and what to look for when hiring them When Big Data is the best approach to use for a project, and when it actually ties analysts’ hands Cutting edge Artificial Intelligence, as well as classical approaches that work better for many problems How many techniques rely on dubious mathematical idealizations, and when you can work around them Perfect for executives who make critical decisions based on data science and analytics, as well as mangers who hire and assess the work of data scientists, Data Science: The Executive Summary also belongs on the bookshelves of salespeople and marketers who need to explain what a data analytics product does. Finally, data scientists themselves will improve their technical work with insights into the goals and constraints of the business situation.
Book Synopsis Amazing Animals: Working Dogs: Summarizing Data 6-Pack by :
Download or read book Amazing Animals: Working Dogs: Summarizing Data 6-Pack written by and published by Teacher Created Materials. This book was released on 2019-06-28 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you ever wondered what it would be like to help someone in need get through their day? Imagine doing it on four paws! Every day, service dogs, therapy dogs, screening dogs, guide dogs, and military working dogs help humans in many ways. Read about the amazing world of working dogs as you learn to summarize data. This math reader integrates math and literacy skills, combining problem solving and real-world connections to help sixth grade students explore mathematics in a meaningful way. Let's Explore Math sidebars and a Problem Solving section provide multiple opportunities for students to practice what they have learned; The DOK-leveled Math Talk section provides rich tasks that facilitate mathematical discourse and promote reasoning and higher-order thinking; Advanced text features develop academic vocabulary and critical literacy skills. This 6-Pack includes six copies of this title and a content-area focused lesson plan.
Book Synopsis Illustrating Statistical Procedures: Finding Meaning in Quantitative Data by : Ray W. Cooksey
Download or read book Illustrating Statistical Procedures: Finding Meaning in Quantitative Data written by Ray W. Cooksey and published by Springer Nature. This book was released on 2020-05-14 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book occupies a unique position in the field of statistical analysis in the behavioural and social sciences in that it targets learners who would benefit from learning more conceptually and less computationally about statistical procedures and the software packages that can be used to implement them. This book provides a comprehensive overview of this important research skill domain with an emphasis on visual support for learning and better understanding. The primary focus is on fundamental concepts, procedures and interpretations of statistical analyses within a single broad illustrative research context. The book covers a wide range of descriptive, correlational and inferential statistical procedures as well as more advanced procedures not typically covered in introductory and intermediate statistical texts. It is an ideal reference for postgraduate students as well as for researchers seeking to broaden their conceptual exposure to what is possible in statistical analysis.
Book Synopsis R Graphics Cookbook by : Winston Chang
Download or read book R Graphics Cookbook written by Winston Chang and published by "O'Reilly Media, Inc.". This book was released on 2013 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Practical recipes for visualizing data"--Cover.
Book Synopsis Summarizing Weather and Climatic Data by : Arnold I. Finklin
Download or read book Summarizing Weather and Climatic Data written by Arnold I. Finklin and published by . This book was released on 1983 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistics with Julia by : Yoni Nazarathy
Download or read book Statistics with Julia written by Yoni Nazarathy and published by Springer Nature. This book was released on 2021-09-04 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph uses the Julia language to guide the reader through an exploration of the fundamental concepts of probability and statistics, all with a view of mastering machine learning, data science, and artificial intelligence. The text does not require any prior statistical knowledge and only assumes a basic understanding of programming and mathematical notation. It is accessible to practitioners and researchers in data science, machine learning, bio-statistics, finance, or engineering who may wish to solidify their knowledge of probability and statistics. The book progresses through ten independent chapters starting with an introduction of Julia, and moving through basic probability, distributions, statistical inference, regression analysis, machine learning methods, and the use of Monte Carlo simulation for dynamic stochastic models. Ultimately this text introduces the Julia programming language as a computational tool, uniquely addressing end-users rather than developers. It makes heavy use of over 200 code examples to illustrate dozens of key statistical concepts. The Julia code, written in a simple format with parameters that can be easily modified, is also available for download from the book’s associated GitHub repository online. See what co-creators of the Julia language are saying about the book: Professor Alan Edelman, MIT: With “Statistics with Julia”, Yoni and Hayden have written an easy to read, well organized, modern introduction to statistics. The code may be looked at, and understood on the static pages of a book, or even better, when running live on a computer. Everything you need is here in one nicely written self-contained reference. Dr. Viral Shah, CEO of Julia Computing: Yoni and Hayden provide a modern way to learn statistics with the Julia programming language. This book has been perfected through iteration over several semesters in the classroom. It prepares the reader with two complementary skills - statistical reasoning with hands on experience and working with large datasets through training in Julia.
Book Synopsis R for Data Science by : Hadley Wickham
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Book Synopsis Measure What Matters by : John Doerr
Download or read book Measure What Matters written by John Doerr and published by Penguin. This book was released on 2018-04-24 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: #1 New York Times Bestseller Legendary venture capitalist John Doerr reveals how the goal-setting system of Objectives and Key Results (OKRs) has helped tech giants from Intel to Google achieve explosive growth—and how it can help any organization thrive. In the fall of 1999, John Doerr met with the founders of a start-up whom he'd just given $12.5 million, the biggest investment of his career. Larry Page and Sergey Brin had amazing technology, entrepreneurial energy, and sky-high ambitions, but no real business plan. For Google to change the world (or even to survive), Page and Brin had to learn how to make tough choices on priorities while keeping their team on track. They'd have to know when to pull the plug on losing propositions, to fail fast. And they needed timely, relevant data to track their progress—to measure what mattered. Doerr taught them about a proven approach to operating excellence: Objectives and Key Results. He had first discovered OKRs in the 1970s as an engineer at Intel, where the legendary Andy Grove ("the greatest manager of his or any era") drove the best-run company Doerr had ever seen. Later, as a venture capitalist, Doerr shared Grove's brainchild with more than fifty companies. Wherever the process was faithfully practiced, it worked. In this goal-setting system, objectives define what we seek to achieve; key results are how those top-priority goals will be attained with specific, measurable actions within a set time frame. Everyone's goals, from entry level to CEO, are transparent to the entire organization. The benefits are profound. OKRs surface an organization's most important work. They focus effort and foster coordination. They keep employees on track. They link objectives across silos to unify and strengthen the entire company. Along the way, OKRs enhance workplace satisfaction and boost retention. In Measure What Matters, Doerr shares a broad range of first-person, behind-the-scenes case studies, with narrators including Bono and Bill Gates, to demonstrate the focus, agility, and explosive growth that OKRs have spurred at so many great organizations. This book will help a new generation of leaders capture the same magic.
Author :National Academies of Sciences, Engineering, and Medicine Publisher :National Academies Press ISBN 13 :0309465370 Total Pages :195 pages Book Rating :4.3/5 (94 download)
Book Synopsis Federal Statistics, Multiple Data Sources, and Privacy Protection by : National Academies of Sciences, Engineering, and Medicine
Download or read book Federal Statistics, Multiple Data Sources, and Privacy Protection written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-01-27 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.
Book Synopsis Concepts of Epidemiology by : Raj S. Bhopal
Download or read book Concepts of Epidemiology written by Raj S. Bhopal and published by Oxford University Press. This book was released on 2016 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: First edition published in 2002. Second edition published in 2008.
Book Synopsis A Programmed Text in Statistics by : J. Hine
Download or read book A Programmed Text in Statistics written by J. Hine and published by . This book was released on 1975 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Computer Programs for Summarizing Climatic Data Stored in the National Fire Weather Data Library by : Larry S. Bradshaw
Download or read book Computer Programs for Summarizing Climatic Data Stored in the National Fire Weather Data Library written by Larry S. Bradshaw and published by . This book was released on 1984 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Introduction to Data Science by : Rafael A. Irizarry
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
