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Using Published Data
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Book Synopsis Using Published Data by : Herbert Jacob
Download or read book Using Published Data written by Herbert Jacob and published by SAGE. This book was released on 1984 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: The apparent authenticity of published data can be as dangerous as it is inviting. This guide points out the main dangers (sampling errors, measurement errors, and invalid or unreliable procedures) and analyzes the various ways in which these problems arise -- giving numerous examples. Jacob discusses ways to solve these problems, and when no solutions seem available, he suggests appropriate disclaimers. An appendix critically evaluates several useful data sets. This monograph also serves as a general reference volume on how to avoid the pitfalls that researchers often overlook. `Its subject is one that should find a place in many more introductory social statistics and research methods texts that it actually does.' -- T
Book Synopsis Handbook on Using Administrative Data for Research and Evidence-based Policy by : Shawn Cole
Download or read book Handbook on Using Administrative Data for Research and Evidence-based Policy written by Shawn Cole and published by Abdul Latif Jameel Poverty Action Lab. This book was released on 2021 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook intends to inform Data Providers and researchers on how to provide privacy-protected access to, handle, and analyze administrative data, and to link them with existing resources, such as a database of data use agreements (DUA) and templates. Available publicly, the Handbook will provide guidance on data access requirements and procedures, data privacy, data security, property rights, regulations for public data use, data architecture, data use and storage, cost structure and recovery, ethics and privacy-protection, making data accessible for research, and dissemination for restricted access use. The knowledge base will serve as a resource for all researchers looking to work with administrative data and for Data Providers looking to make such data available.
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, Use, Improve! by : Christina A. Russell
Download or read book Measure, Use, Improve! written by Christina A. Russell and published by IAP. This book was released on 2020-10-01 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: Measure, Use, Improve! Data Use in Out-of-School Time shares the experience and wisdom from a broad cross-section of out-of-school time professionals, ranging from internal evaluators, to funders, to researchers, to policy advocates. Key themes of the volume include building support for learning and evaluation within out-of-school time programs, creating and sustaining continuous quality improvement efforts, authentically engaging young people and caregivers in evaluation, and securing funder support for learning and evaluation. This volume will be particularly useful to leadership-level staff in out-of-school time organizations that are thinking about deepening their own learning and evaluation systems, yet aren’t sure where to start. Authors share conceptual frameworks that have helped inform their thinking, walk through practical examples of how they use data in out-of-school time, and offer advice to colleagues.
Book Synopsis Cochrane Handbook for Systematic Reviews of Interventions by : Julian P. T. Higgins
Download or read book Cochrane Handbook for Systematic Reviews of Interventions written by Julian P. T. Higgins and published by Wiley. This book was released on 2008-11-24 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves.
Book Synopsis Statistical Methods in Water Resources by : D.R. Helsel
Download or read book Statistical Methods in Water Resources written by D.R. Helsel and published by Elsevier. This book was released on 1993-03-03 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data on water quality and other environmental issues are being collected at an ever-increasing rate. In the past, however, the techniques used by scientists to interpret this data have not progressed as quickly. This is a book of modern statistical methods for analysis of practical problems in water quality and water resources.The last fifteen years have seen major advances in the fields of exploratory data analysis (EDA) and robust statistical methods. The 'real-life' characteristics of environmental data tend to drive analysis towards the use of these methods. These advances are presented in a practical and relevant format. Alternate methods are compared, highlighting the strengths and weaknesses of each as applied to environmental data. Techniques for trend analysis and dealing with water below the detection limit are topics covered, which are of great interest to consultants in water-quality and hydrology, scientists in state, provincial and federal water resources, and geological survey agencies.The practising water resources scientist will find the worked examples using actual field data from case studies of environmental problems, of real value. Exercises at the end of each chapter enable the mechanics of the methodological process to be fully understood, with data sets included on diskette for easy use. The result is a book that is both up-to-date and immediately relevant to ongoing work in the environmental and water sciences.
Book Synopsis Analyzing Qualitative Data with MAXQDA by : Udo Kuckartz
Download or read book Analyzing Qualitative Data with MAXQDA written by Udo Kuckartz and published by Springer. This book was released on 2019-05-31 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents strategies for analyzing qualitative and mixed methods data with MAXQDA software, and provides guidance on implementing a variety of research methods and approaches, e.g. grounded theory, discourse analysis and qualitative content analysis, using the software. In addition, it explains specific topics, such as transcription, building a coding frame, visualization, analysis of videos, concept maps, group comparisons and the creation of literature reviews. The book is intended for masters and PhD students as well as researchers and practitioners dealing with qualitative data in various disciplines, including the educational and social sciences, psychology, public health, business or economics.
Book Synopsis Data Collection Research Methods in Applied Linguistics by : Heath Rose
Download or read book Data Collection Research Methods in Applied Linguistics written by Heath Rose and published by Bloomsbury Publishing. This book was released on 2019-11-28 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The successful collection of data is a key challenge to obtaining reliable and valid results in applied linguistics research. Data Collection Research Methods in Applied Linguistics investigates how research is conducted in the field, encompassing the challenges and obstacles applied linguists face in collecting good data. The book explores frequently used data collection techniques, including: * interviews and focus groups * observations * stimulated recall and think aloud protocols * data elicitation tasks * corpus methods * questionnaires * validated tests and measures Each chapter focuses on one type of data collection, outlining key concepts, threats to reliability and validity, procedures for good data collection, and implications for researchers. The chapters also include exemplary research projects, showcasing and explaining for readers how the technique was used to collect data in a successfully published study. This book is an essential resource for both novice and experienced applied linguists tackling data collection techniques for the first time.
Book Synopsis Data Analysis for Business, Economics, and Policy by : Gábor Békés
Download or read book Data Analysis for Business, Economics, and Policy written by Gábor Békés and published by Cambridge University Press. This book was released on 2021-05-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Book Synopsis An Introduction to Statistical Learning by : Gareth James
Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Book Synopsis Humanities Data Analysis by : Folgert Karsdorp
Download or read book Humanities Data Analysis written by Folgert Karsdorp and published by Princeton University Press. This book was released on 2021-01-12 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations
Book Synopsis Introduction to Privacy-Preserving Data Publishing by : Benjamin C.M. Fung
Download or read book Introduction to Privacy-Preserving Data Publishing written by Benjamin C.M. Fung and published by CRC Press. This book was released on 2010-08-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Int
Book Synopsis Sharing Clinical Trial Data by : Institute of Medicine
Download or read book Sharing Clinical Trial Data written by Institute of Medicine and published by National Academies Press. This book was released on 2015-04-20 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.
Book Synopsis Measuring Scholarly Impact by : Ying Ding
Download or read book Measuring Scholarly Impact written by Ying Ding and published by Springer. This book was released on 2014-11-06 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an authoritative handbook of current topics, technologies and methodological approaches that may be used for the study of scholarly impact. The included methods cover a range of fields such as statistical sciences, scientific visualization, network analysis, text mining, and information retrieval. The techniques and tools enable researchers to investigate metric phenomena and to assess scholarly impact in new ways. Each chapter offers an introduction to the selected topic and outlines how the topic, technology or methodological approach may be applied to metrics-related research. Comprehensive and up-to-date, Measuring Scholarly Impact: Methods and Practice is designed for researchers and scholars interested in informetrics, scientometrics, and text mining. The hands-on perspective is also beneficial to advanced-level students in fields from computer science and statistics to information science.
Book Synopsis Data Modeling with Tableau by : Kirk Munroe
Download or read book Data Modeling with Tableau written by Kirk Munroe and published by Packt Publishing Ltd. This book was released on 2022-12-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Save time analyzing volumes of data using best practices to extract, model, and create insights from your data Key FeaturesMaster best practices in data modeling with Tableau Prep Builder and Tableau DesktopApply Tableau Server and Cloud to create and extend data modelsBuild organizational data models based on data and content governance best practicesBook Description Tableau is unlike most other BI platforms that have a single data modeling tool and enterprise data model (for example, LookML from Google's Looker). That doesn't mean Tableau doesn't have enterprise data governance; it is both robust and very flexible. This book will help you build a data-driven organization with the proper use of Tableau governance models. Data Modeling with Tableau is an extensive guide, complete with step-by-step explanations of essential concepts, practical examples, and hands-on exercises. As you progress through the chapters, you will learn the role that Tableau Prep Builder and Tableau Desktop each play in data modeling. You'll also explore the components of Tableau Server and Cloud that make data modeling more robust, secure, and performant. Moreover, by extending data models for Ask and Explain Data, you'll gain the knowledge required to extend analytics to more people in their organizations, leading to better data-driven decisions. Finally, this book will get into the entire Tableau stack and get the techniques required to build the right level of governance into Tableau data models for the right use cases. By the end of this Tableau book, you'll have a firm understanding of how to leverage data modeling in Tableau to benefit your organization. What you will learnShowcase Tableau published data sources and embedded connectionsApply Ask Data in data cataloging and natural language queryExhibit features of Tableau Prep Builder with hands-on exercisesModel data with Tableau Desktop through examplesFormulate a governed data strategy using Tableau Server and CloudOptimize data models for Ask and Explain DataWho this book is for This book is for data analysts and business analysts who are looking to expand their data skills, offering a broad foundation to build better data models in Tableau for easier analysis and better query performance. It will also benefit individuals responsible for making trusted and secure data available to their organization through Tableau, such as data stewards and others who work to take enterprise data and make it more accessible to business analysts.
Book Synopsis Introduction to Statistics and Data Analysis by : Christian Heumann
Download or read book Introduction to Statistics and Data Analysis written by Christian Heumann and published by Springer Nature. This book was released on 2023-01-30 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Book Synopsis Statistical Analysis of Network Data by : Eric D. Kolaczyk
Download or read book Statistical Analysis of Network Data written by Eric D. Kolaczyk and published by Springer Science & Business Media. This book was released on 2009-04-20 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
