Download or read book Data Analytics Common Core written by Eric Gaze and published by . This book was released on 2025-01-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Science for Undergraduates written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-11-11 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.
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
Download or read book Data Analytics and Psychometrics written by Hong Jiao and published by IAP. This book was released on 2018-12-01 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general theme of this book is to encourage the use of relevant methodology in data mining which is or could be applied to the interplay of education, statistics and computer science to solve psychometric issues and challenges in the new generation of assessments. In addition to item response data, other data collected in the process of assessment and learning will be utilized to help solve psychometric challenges and facilitate learning and other educational applications. Process data include those collected or available for collection during the process of assessment and instructional phase such as responding sequence data, log files, the use of help features, the content of web searches, etc. Some book chapters present the general exploration of process data in large-scale assessment. Further, other chapters also address how to integrate psychometrics and learning analytics in assessment and survey, how to use data mining techniques for security and cheating detection, how to use more assessment results to facilitate student’s learning and guide teacher’s instructional efforts. The book includes both theoretical and methodological presentations that might guide the future in this area, as well as illustrations of efforts to implement big data analytics that might be instructive to those in the field of learning and psychometrics. The context of the effort is diverse, including K-12, higher education, financial planning, and survey utilization. It is hoped that readers can learn from different disciplines, especially those who are specialized in assessment, would be critical to expand the ideas of what we can do with data analytics for informing assessment practices.
Download or read book Principles and Standards for School Mathematics written by and published by . This book was released on 2000 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-read summary is an excellent tool for introducing others to the messages contained in Principles and Standards.
Download or read book Bridging the Gap Between Common Core State Standards and Teaching Statistics written by Patrick Hopfensperger and published by . This book was released on 2012 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Learn Data Analytics for Beginners to Core Advance written by Janani Sathish and published by Independently Published. This book was released on 2021-05 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science has taken the planet by storm. Every field of study and area of business has been affected as people increasingly realize the worth of the incredible quantities of knowledge being generated. But to extract value from those data, one must be trained within the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it a useful tool for data scientists round the world. This book is about the basics of R programming. you'll start with the fundamentals of the language, find out how to control datasets, the way to write functions, and the way to debug and optimize code. With the basics provided during this book, you'll have a solid foundation on which to create your data science toolbox. during this book you'll learn what you would like to understand to start assembling and leading a knowledge science enterprise, albeit you've got never worked in data science before. You'll get a crash program in data science in order that you'll be familiar with the sector and understand your role as a pacesetter . You'll also find out how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the info science pipeline, the goals of every stage, and the way to stay your team on track throughout. Finally, you'll learn some down-to-earth practical skills which will assist you overcome the common challenges that regularly derail data science projects Reproducibility is that the concept data analyses should be published or made available with their data and software code in order that others may verify the findings and repose on them.
Download or read book The Common Core Companion The Standards Decoded Grades 6 8 written by Jim Burke and published by Corwin Press. This book was released on 2013-08-30 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: That version of the standards you wish you had All over the nation, teachers and administrators are poring over the Common Core State Standards to come up with meaningful plans for raising student achievement. But as clear as the standards are, they are more of a sundial than a GPS for pinpointing just what to teach and how to teach it. Enter Jim Burke with The Common Core Companion: The Standards Decoded, Grades 6-8. It's that version of the standards you wish you had: a roadmap of what each standard says, what each standard means, and how precisely to put that standard into day-to-day practice across English Language Arts, Social Studies, Science, and Technical Subjects. Designed to provide schools, districts, and departments with a common language or set of reference points for effective school-wide implementation, The Common Core Companion clearly lays out: Grades 6-8 standards side by side with key distinctions highlighted so teachers know what they must teach from grade to grade All the different content-area versions of each standard arranged on one page to facilitate easy reference and school wide collaboration Explanations of each standard on a corresponding page, written in accessible language, along with prompts and questions to help students learn and apply each standard Essential content to cover and lesson ideas for modeling the literacy skills behind the standards Instructional techniques for each standard based on Jim's extensive teaching experience and current research on effective instruction Complete glossary for each standard and adaptations for ELL students Don't spend another minute poring over the standards. Jim has already done that for you. Focus instead on how to teach them, using The Common Core Companion as your one-stop guide for teaching, planning, assessing, collaborating, and designing powerful reading and writing curricula.
Download or read book The Data Science Handbook written by Field Cady and published by John Wiley & Sons. This book was released on 2017-02-28 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of data science covering the analytics, programming, and business skills necessary to master the discipline Finding a good data scientist has been likened to hunting for a unicorn: the required combination of technical skills is simply very hard to find in one person. In addition, good data science is not just rote application of trainable skill sets; it requires the ability to think flexibly about all these areas and understand the connections between them. This book provides a crash course in data science, combining all the necessary skills into a unified discipline. Unlike many analytics books, computer science and software engineering are given extensive coverage since they play such a central role in the daily work of a data scientist. The author also describes classic machine learning algorithms, from their mathematical foundations to real-world applications. Visualization tools are reviewed, and their central importance in data science is highlighted. Classical statistics is addressed to help readers think critically about the interpretation of data and its common pitfalls. The clear communication of technical results, which is perhaps the most undertrained of data science skills, is given its own chapter, and all topics are explained in the context of solving real-world data problems. The book also features: • Extensive sample code and tutorials using Python™ along with its technical libraries • Core technologies of “Big Data,” including their strengths and limitations and how they can be used to solve real-world problems • Coverage of the practical realities of the tools, keeping theory to a minimum; however, when theory is presented, it is done in an intuitive way to encourage critical thinking and creativity • A wide variety of case studies from industry • Practical advice on the realities of being a data scientist today, including the overall workflow, where time is spent, the types of datasets worked on, and the skill sets needed The Data Science Handbook is an ideal resource for data analysis methodology and big data software tools. The book is appropriate for people who want to practice data science, but lack the required skill sets. This includes software professionals who need to better understand analytics and statisticians who need to understand software. Modern data science is a unified discipline, and it is presented as such. This book is also an appropriate reference for researchers and entry-level graduate students who need to learn real-world analytics and expand their skill set. FIELD CADY is the data scientist at the Allen Institute for Artificial Intelligence, where he develops tools that use machine learning to mine scientific literature. He has also worked at Google and several Big Data startups. He has a BS in physics and math from Stanford University, and an MS in computer science from Carnegie Mellon.
Download or read book Classification Evaluation of the 1994 95 Common Core of Data written by Stephen Owens and published by Department of Education Office of Educational. This book was released on 1999 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report contributes to the comprehensive evaluation of the Common Core of Data (CCD) program by providing an analysis of CCD definitions in order to identify potential classification problems. At the time of the evaluation, the CCD program consisted of four surveys. The focus of this evaluation is on the "Public Elementary/Secondary Education Agency Survey." The evaluation process was initiated by researching state statutes and administrative codes to determine the powers, governance, and services provided by agencies in each state. A detailed analysis of CCD definitions reveals that these definitions are generally inadequate. Many are neither exhaustive nor inclusive. The inadequacy and misinterpretation of these definitions leads to unreliable and invalid data. CCD definitions often do not draw a clear distinction between school and agency surveys. The definitions should be revised to be flexible and exhaustive, with clear documentation and explanation provided for instances in which individual arrangements in states differ from conventional approaches. All education surveys that use CCD definitions as their sampling frame should be coordinated. Changes are especially needed in the areas of enrollment and geographic coding. (Contains two tables.) (SLD)
Download or read book California Common Core State Standards written by California. Department of Education and published by . This book was released on 2013 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A General Introduction to Data Analytics written by João Moreira and published by John Wiley & Sons. This book was released on 2018-07-18 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming A General Introduction to Data Analytics is an essential guide to understand and use data analytics. This book is written using easy-to-understand terms and does not require familiarity with statistics or programming. The authors—noted experts in the field—highlight an explanation of the intuition behind the basic data analytics techniques. The text also contains exercises and illustrative examples. Thought to be easily accessible to non-experts, the book provides motivation to the necessity of analyzing data. It explains how to visualize and summarize data, and how to find natural groups and frequent patterns in a dataset. The book also explores predictive tasks, be them classification or regression. Finally, the book discusses popular data analytic applications, like mining the web, information retrieval, social network analysis, working with text, and recommender systems. The learning resources offer: A guide to the reasoning behind data mining techniques A unique illustrative example that extends throughout all the chapters Exercises at the end of each chapter and larger projects at the end of each of the text’s two main parts Together with these learning resources, the book can be used in a 13-week course guide, one chapter per course topic. The book was written in a format that allows the understanding of the main data analytics concepts by non-mathematicians, non-statisticians and non-computer scientists interested in getting an introduction to data science. A General Introduction to Data Analytics is a basic guide to data analytics written in highly accessible terms.
Download or read book Handbook of Data Analysis written by Melissa A Hardy and published by SAGE. This book was released on 2009-06-17 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: ′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
Download or read book Driven by Data written by Paul Bambrick-Santoyo and published by Jossey-Bass. This book was released on 2010-03-10 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Driven by Data offers valuable tips and general guidelines about data-based methods and the difficulties surrounding the implementation of data-driven instruction. Through a CD-ROM, this guidebook provides all the tools needed to launch data-driven instruction effectively, such as an implementation rubric, meeting agendas, calendars, assessment templates, and more. Written by Paul Bambrick-Santoyo, who has worked with over 1,000 schools across the nation, the book clearly shows how to maneuver through assessments and statistics. Bambrick-Santoyo offers vital tips, such as: how to create a data culture, how to run a successful data analysis meeting, how to write quality assessments, and how to deal with resistance from your teachers. The book also includes twenty case studies of high-performing schools. School leaders will find this resource useful for achieving remarkable results and immense gains, regardless of the school's background, leader, or demographic. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
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 Analytic Literacy written by Andrew Banasiewicz and published by Walter de Gruyter GmbH & Co KG. This book was released on 2023-07-24 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The explosive growth in volume and varieties of data generated by the seemingly endless arrays of digital systems and applications is rapidly elevating the importance of being able to utilize data; in fact, data analytic literacy is becoming as important now, at the onset of the Digital Era, as rudimentary literacy and numeracy were throughout the Industrial Era. And yet, what constitutes data analytic literacy is poorly understood. To some, data analytic literacy is the ability to use basic statistics, to others it is data science ‘light’, and to still others it is just general familiarity with common data analytic outcomes. Exploring the scope and the structure of rudimentary data analytic competencies is at the core of this book which takes the perspective that data analytics is a new and distinct domain of knowledge and practice. It offers application-minded framing of rudimentary data analytic competencies built around conceptually sound and practically meaningful processes and mechanics of systematically transforming messy and heterogeneous data into informative insights. Data Analytic Literacy is meant to offer an easy-to-follow overview of the critical elements of the reasoning behind basic data manipulation and analysis approaches and steps, coupled with the commonly used data analytic and data communication techniques and tools. It offers an all-inclusive guide to developing basic data analytic competencies.
Download or read book Data Analytics for Discourse Analysis with Python written by Dennis Tay and published by Taylor & Francis. This book was released on 2024-04-19 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise volume, using examples of psychotherapy talk, showcases the potential applications of data analytics for advancing discourse research and other related disciplines. The book provides a brief primer on data analytics, defined as the science of analyzing raw data to reveal new insights and support decision making. Currently underutilized in discourse research, Tay draws on the case of psychotherapy talk, in which clients’ concerns are worked through via verbal interaction with therapists, to demonstrate how data analytics can address both practical and theoretical concerns. Each chapter follows a consistent structure, offering a streamlined walkthrough of a key technique, an example case study, and annotated Python code. The volume shows how techniques such as simulations, classification, clustering, and time series analysis can address such issues as incomplete data transcripts, therapist–client (a)synchrony, and client prognosis, offering inspiration for research, training, and practitioner self-reflection in psychotherapy and other discourse contexts. This volume is a valuable resource for discourse and linguistics researchers, particularly for those interested in complementary approaches to qualitative methods, as well as active practitioners.
