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Data Handling Skills
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Book Synopsis Principles of Statistical Data Handling by : Fred Davidson
Download or read book Principles of Statistical Data Handling written by Fred Davidson and published by SAGE Publications, Incorporated. This book was released on 1996-04-09 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Statistical Data Handling is designed to help readers understand the principles of data handling so that they can make better use of computer data in research or study.
Book Synopsis Data-Handling in Biomedical Science by : Peter White
Download or read book Data-Handling in Biomedical Science written by Peter White and published by Cambridge University Press. This book was released on 2010-05-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Packed with worked examples and problems, this book will help the reader improve their confidence and skill in data-handling. The mathematical methods needed for problem-solving are described in the first part of the book, with chapters covering topics such as indices, graphs and logarithms. The following eight chapters explore data-handling in different areas of microbiology and biochemistry including microbial growth, enzymes and radioactivity. Each chapter is fully illustrated with worked examples that provide a step-by-step guide to the solution of the most common problems. Over 30 exercises, ranging in difficulty and length, allow you to practise your skills and are accompanied by a full set of hints and solutions.
Book Synopsis Data Management for Researchers by : Kristin Briney
Download or read book Data Management for Researchers written by Kristin Briney and published by Pelagic Publishing Ltd. This book was released on 2015-09-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to everything scientists need to know about data management, this book is essential for researchers who need to learn how to organize, document and take care of their own data. Researchers in all disciplines are faced with the challenge of managing the growing amounts of digital data that are the foundation of their research. Kristin Briney offers practical advice and clearly explains policies and principles, in an accessible and in-depth text that will allow researchers to understand and achieve the goal of better research data management. Data Management for Researchers includes sections on: * The data problem – an introduction to the growing importance and challenges of using digital data in research. Covers both the inherent problems with managing digital information, as well as how the research landscape is changing to give more value to research datasets and code. * The data lifecycle – a framework for data’s place within the research process and how data’s role is changing. Greater emphasis on data sharing and data reuse will not only change the way we conduct research but also how we manage research data. * Planning for data management – covers the many aspects of data management and how to put them together in a data management plan. This section also includes sample data management plans. * Documenting your data – an often overlooked part of the data management process, but one that is critical to good management; data without documentation are frequently unusable. * Organizing your data – explains how to keep your data in order using organizational systems and file naming conventions. This section also covers using a database to organize and analyze content. * Improving data analysis – covers managing information through the analysis process. This section starts by comparing the management of raw and analyzed data and then describes ways to make analysis easier, such as spreadsheet best practices. It also examines practices for research code, including version control systems. * Managing secure and private data – many researchers are dealing with data that require extra security. This section outlines what data falls into this category and some of the policies that apply, before addressing the best practices for keeping data secure. * Short-term storage – deals with the practical matters of storage and backup and covers the many options available. This section also goes through the best practices to insure that data are not lost. * Preserving and archiving your data – digital data can have a long life if properly cared for. This section covers managing data in the long term including choosing good file formats and media, as well as determining who will manage the data after the end of the project. * Sharing/publishing your data – addresses how to make data sharing across research groups easier, as well as how and why to publicly share data. This section covers intellectual property and licenses for datasets, before ending with the altmetrics that measure the impact of publicly shared data. * Reusing data – as more data are shared, it becomes possible to use outside data in your research. This chapter discusses strategies for finding datasets and lays out how to cite data once you have found it. This book is designed for active scientific researchers but it is useful for anyone who wants to get more from their data: academics, educators, professionals or anyone who teaches data management, sharing and preservation. "An excellent practical treatise on the art and practice of data management, this book is essential to any researcher, regardless of subject or discipline." —Robert Buntrock, Chemical Information Bulletin
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 Data Handling and Analysis by : Andrew D. Blann
Download or read book Data Handling and Analysis written by Andrew D. Blann and published by Oxford University Press, USA. This book was released on 2015 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Handling and Analysis provides a broad review of the quantitative skills needed to be an effective biomedical scientist.
Book Synopsis Handling Qualitative Data by : Lyn Richards
Download or read book Handling Qualitative Data written by Lyn Richards and published by SAGE. This book was released on 2009-11-18 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lecturers, click here to request an e-inspection copy of this text This new edition of Lyn Richards' best-selling book provides an accessible introduction to qualitative research for students and practitioners. Recognizing that for many new researchers dealing with data is the main point of departure, this book helps them to acquire a progressive understanding of the skills and methodological issues that are central to qualitative research. Lyn Richards provides clear and pragmatic guidance on how to handle, reflect on and get results from small amounts of data, while at the same time showing how a consideration of methods and their philosophical underpinnings informs how we should best handle our data. This book also covers all the processes of making, meeting, sorting, coding, documenting and exploring qualitative data, smoothly integrating software use and the discussion of the main challenges that readers are likely to encounter. It guides novice researchers to achieve valid and useful outcomes from qualitative analysis, and to ensure they do justice to their data. This second edition features: - Increased coverage of issues about the researcher's relation to their data and ethical implications - An expanded section on preparing for data collection and reflecting on the nature of data. There is also a brand new website, offering: - Live, detailed case studies of qualitative methods in practice, linking to publications and illustrative material. Researchers tell the stories of projects, from design, through what was actually done with the data, to how analysis was achieved and reported; - A software guide with links to information and tutorials in several products.
Book Synopsis Knowledge Graphs and Big Data Processing by : Valentina Janev
Download or read book Knowledge Graphs and Big Data Processing written by Valentina Janev and published by Springer Nature. This book was released on 2020-07-15 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
Book Synopsis The Data Librarian’s Handbook by : Robin Rice
Download or read book The Data Librarian’s Handbook written by Robin Rice and published by Facet Publishing. This book was released on 2016-12-20 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: An insider’s guide to data librarianship packed full of practical examples and advice for any library and information professional learning to deal with data. Interest in data has been growing in recent years. Support for this peculiar class of digital information – its use, preservation and curation, and how to support researchers’ production and consumption of it in ever greater volumes to create new knowledge, is needed more than ever. Many librarians and information professionals are finding their working life is pulling them toward data support or research data management but lack the skills required. The Data Librarian’s Handbook, written by two data librarians with over 30 years’ combined experience, unpicks the everyday role of the data librarian and offers practical guidance on how to collect, curate and crunch data for economic, social and scientific purposes. With contemporary case studies from a range of institutions and disciplines, tips for best practice, study aids and links to key resources, this book is a must-read for all new entrants to the field, library and information students and working professionals. Key topics covered include: • the evolution of data libraries and data archives • handling data compared to other forms of information • managing and curating data to ensure effective use and longevity • how to incorporate data literacy into mainstream library instruction and information literacy training • how to develop an effective institutional research data management (RDM) policy and infrastructure • how to support and review a data management plan (DMP) for a project, a key requirement for most research funders • approaches for developing, managing and promoting data repositories • handling and sharing confidential or sensitive data • supporting open scholarship and open science, ensuring data are discoverable, accessible, intelligible and assessable. This title is for the practising data librarian, possibly new in their post with little experience of providing data support. It is also for managers and policy-makers, public service librarians, research data management coordinators and data support staff. It will also appeal to students and lecturers in iSchools and other library and information degree programmes where academic research support is taught.
Book Synopsis Bioinformatics Data Skills by : Vince Buffalo
Download or read book Bioinformatics Data Skills written by Vince Buffalo and published by "O'Reilly Media, Inc.". This book was released on 2015-07 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the data skills necessary for turning large sequencing datasets into reproducible and robust biological findings. With this practical guide, youâ??ll learn how to use freely available open source tools to extract meaning from large complex biological data sets. At no other point in human history has our ability to understand lifeâ??s complexities been so dependent on our skills to work with and analyze data. This intermediate-level book teaches the general computational and data skills you need to analyze biological data. If you have experience with a scripting language like Python, youâ??re ready to get started. Go from handling small problems with messy scripts to tackling large problems with clever methods and tools Process bioinformatics data with powerful Unix pipelines and data tools Learn how to use exploratory data analysis techniques in the R language Use efficient methods to work with genomic range data and range operations Work with common genomics data file formats like FASTA, FASTQ, SAM, and BAM Manage your bioinformatics project with the Git version control system Tackle tedious data processing tasks with with Bash scripts and Makefiles
Download or read book Career Renewal written by Stephen Rosen and published by Academic Press. This book was released on 1998 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This guide will help you find a satisfying career in today's market. It includes numerous assessment surveys, identifies career resources for professional networking, outlines how to write a winning resume, and features numerous personal case histories of those who have successfully made the transition from academia to the business world. The authors' step-by-step techniques have been field-tested on thousands and will help you to discover new career perspectives.
Book Synopsis Teaching and Learning Geography by : Daniella Tilbury
Download or read book Teaching and Learning Geography written by Daniella Tilbury and published by Routledge. This book was released on 2002-11 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear overview of current thinking on the teaching and learning of geography. It is ideal for anyone beginning a career in teaching the subject in schools. The chapters are written by experienced teachers.
Book Synopsis Essential Primary Mathematics by : Caroline Rickard
Download or read book Essential Primary Mathematics written by Caroline Rickard and published by McGraw-Hill Education (UK). This book was released on 2013-05-16 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are teaching or learning to teach primary mathematics, this is the toolkit to support you! Not only does it cover the essential knowledge and understanding that you and your pupils need to know, it also offers 176 great ideas for teaching primary mathematics - adaptable for use within different areas of mathematics and for different ages and abilities. Tackling children’s misconceptions in each topic area and differentiation through open-ended tasks and elements of choice, the book encourages you to think deeply about the teaching of the primary mathematics curriculum. The classroom activities, which are simple to resource and use, support you in meeting the Teachers’ Standards securely and encourage children to: Think deeply about mathematics and to challenge themselves Develop mathematical independence Engage in mathematical talk Work collaboratively with others to further understanding Whether you are just getting started in your teaching career or more experienced you will find a wealth of innovative activities to support you in teaching primary mathematics in effective and creative ways. "This book is an absolute must for every primary teacher. The perfect blend of subject knowledge, common misconceptions, pupil activities and self-assessment questions will support all those who are feeling slightly less than confident about teaching a mathematical topic. It will also be invaluable to experienced teachers and subject leaders who wish to think more deeply about how to teach mathematics effectively." Sue Davis, Primary PGCE Course Leader and Lecturer in Mathematics Education, University of Leicester, UK "This book has the conversational style of an excellent mentor and/or tutor of primary mathematics. It offers advice and guidance on how to be an effective teacher of mathematics whilst still drawing the reader’s attention to the importance of developing good subject knowledge, and how this can be addressed. Mathematical concepts are explained with reference to their theoretical underpinning and are then set in the context of real learning opportunities that illustrate good pedagogy. There is a real emphasis on teaching for learning, and this is most evident in the introductory chapter which provides a brief discussion of the big issues currently being debated in the field of primary mathematics. The consistent format of the subject chapters supports the reader’s ability to plan and teach a wide range of appropriate activities based on rich mathematics. These are all neatly illustrated by children’s drawings which bring the book to life.This is an all encompassing text for any student or teacher of mathematics and will feature on my highly recommended reading list." Paula Stone, Senior Lecturer Primary Education (Mathematics), Canterbury Christ Church University, UK "This book is ideal for student and practicing teachers alike. The user-friendly format such as the overview of contents at the beginning of each chapter and the highlighting of key misconceptions in each area, make it easy to locate relevant information. Each chapter evolves logically through subject knowledge and progression in learning for children. This book stands out from other texts I have used as there is an extremely helpful section at the end of each chapter which provides suggested classroom activities with associated learning objectives for each area of mathematics. As a final year student, I only wish this book had been available to me at the beginning of my course!" Shelley Rogers, Student Teacher, University of Chichester, UK "This book approaches the teaching of primary mathematics with a clear ethos, which is explained in the first chapter and then pervades all the suggestions and discussions which follow. The author deals with issues such as turning children’s misconceptions and ‘mistakes’ into learning opportunities, provoking the children into communicating their reasoning and differentiating lessons in ways that empower rather than categorise children. The author’s experience of having taught and observed hundreds of mathematics lessons is distilled into the essence of primary mathematics teaching." Dr Marcus Witt, Senior Lecturer in Primary and Early Years Mathematics Education, University of the West of England, UK "The theory sections of the book are really detailed which helps to provide a secure knowledge base for teaching primary mathematics. I especially like the way that the book is laid out; it is really easy to navigate. I love how the common misconceptions are outlined and explained in boxes separate to the body of the text but are also re-listed at the end of a chapter so that you could revise the potential issues which may arise before you start to teach a particular topic. The activities are well organised and adaptable but it is useful to see which age range each activity is suggested for at a glance, alongside the learning objective." Natalie Ridler, NQT
Book Synopsis Data Clean-Up and Management by : Margaret Hogarth
Download or read book Data Clean-Up and Management written by Margaret Hogarth and published by Elsevier. This book was released on 2012-10-22 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data use in the library has specific characteristics and common problems. Data Clean-up and Management addresses these, and provides methods to clean up frequently-occurring data problems using readily-available applications. The authors highlight the importance and methods of data analysis and presentation, and offer guidelines and recommendations for a data quality policy. The book gives step-by-step how-to directions for common dirty data issues. - Focused towards libraries and practicing librarians - Deals with practical, real-life issues and addresses common problems that all libraries face - Offers cradle-to-grave treatment for preparing and using data, including download, clean-up, management, analysis and presentation
Book Synopsis Learning to Teach by : Gill Nicholls
Download or read book Learning to Teach written by Gill Nicholls and published by Routledge. This book was released on 2014-05-12 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in accordance with the Teacher Training Association and DfEE guidelines, this text is intended to become a course reference. The author examines all modules which need to be studied in teacher training programmes and takes account of the Labour government's plans for teacher education.
Book Synopsis The Medical Library Association Guide to Data Management for Librarians by : Lisa Federer
Download or read book The Medical Library Association Guide to Data Management for Librarians written by Lisa Federer and published by Rowman & Littlefield. This book was released on 2016-09-15 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological advances and the rise of collaborative, interdisciplinary approaches have changed the practice of research. The 21st century researcher not only faces the challenge of managing increasingly complex datasets, but also new data sharing requirements from funders and journals. Success in today’s research enterprise requires an understanding of how to work effectively with data, yet most researchers have never had any formal training in data management. Libraries have begun developing services and programs to help researchers meet the demands of the data-driven research enterprise, giving librarians exciting new opportunities to use their expertise and skills. The Medical Library Association Guide to Data Management for Librarians highlights the many ways that librarians are addressing researchers’ changing needs at a variety of institutions, including academic, hospital, and government libraries. Each chapter ends with “pearls of wisdom,” a bulleted list of 5-10 takeaway messages from the chapter that will help readers quickly put the ideas from the chapter into practice. From theoretical foundations to practical applications, this book provides a background for librarians who are new to data management as well as new ideas and approaches for experienced data librarians.
Book Synopsis The Data Science Framework by : Juan J. Cuadrado-Gallego
Download or read book The Data Science Framework written by Juan J. Cuadrado-Gallego and published by Springer Nature. This book was released on 2020-10-01 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines.
Book Synopsis Best Practices in Data Cleaning by : Jason W. Osborne
Download or read book Best Practices in Data Cleaning written by Jason W. Osborne and published by SAGE. This book was released on 2013 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean data. This book provides a clear, step-by-step process of examining and cleaning data in order to decrease error rates and increase both the power and replicability of results. Jason W. Osborne, author of Best Practices in Quantitative Methods (SAGE, 2008) provides easily-implemented suggestions that are research-based and will motivate change in practice by empirically demonstrating, for each topic, the benefits of following best practices and the potential consequences of not following these guidelines. If your goal is to do the best research you can do, draw conclusions that are most likely to be accurate representations of the population(s) you wish to speak about, and report results that are most likely to be replicated by other researchers, then this basic guidebook will be indispensible.
