Practical Data Handling

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Practical Data Analysis in Chemistry

Author : Marcel Maeder
Publisher : Elsevier
ISBN 13 : 0080548830
Total Pages : 341 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Practical Data Analysis in Chemistry by : Marcel Maeder

Download or read book Practical Data Analysis in Chemistry written by Marcel Maeder and published by Elsevier. This book was released on 2007-08-10 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses.* Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes.* Provides examples of routines that are easily adapted to the processes investigated by the reader* 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

Principles of Statistical Data Handling

Author : Fred Davidson
Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 344 pages
Book Rating : 4.F/5 ( download)

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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.

Practical Guide to Clinical Data Management

Author : Susanne Prokscha
Publisher : CRC Press
ISBN 13 : 1420007882
Total Pages : 254 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Practical Guide to Clinical Data Management by : Susanne Prokscha

Download or read book Practical Guide to Clinical Data Management written by Susanne Prokscha and published by CRC Press. This book was released on 2006-08-01 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: The management of clinical data, from its collection to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. As its importance has grown, clinical data management (CDM) has changed from an essentially clerical task in the late 1970s and early 1980s t

Practical Real-time Data Processing and Analytics

Author : Shilpi Saxena
Publisher : Packt Publishing Ltd
ISBN 13 : 1787289869
Total Pages : 354 pages
Book Rating : 4.7/5 (872 download)

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Book Synopsis Practical Real-time Data Processing and Analytics by : Shilpi Saxena

Download or read book Practical Real-time Data Processing and Analytics written by Shilpi Saxena and published by Packt Publishing Ltd. This book was released on 2017-09-28 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to help you tackle different real-time data processing and analytics problems using the best tools for each scenario About This Book Learn about the various challenges in real-time data processing and use the right tools to overcome them This book covers popular tools and frameworks such as Spark, Flink, and Apache Storm to solve all your distributed processing problems A practical guide filled with examples, tips, and tricks to help you perform efficient Big Data processing in real-time Who This Book Is For If you are a Java developer who would like to be equipped with all the tools required to devise an end-to-end practical solution on real-time data streaming, then this book is for you. Basic knowledge of real-time processing would be helpful, and knowing the fundamentals of Maven, Shell, and Eclipse would be great. What You Will Learn Get an introduction to the established real-time stack Understand the key integration of all the components Get a thorough understanding of the basic building blocks for real-time solution designing Garnish the search and visualization aspects for your real-time solution Get conceptually and practically acquainted with real-time analytics Be well equipped to apply the knowledge and create your own solutions In Detail With the rise of Big Data, there is an increasing need to process large amounts of data continuously, with a shorter turnaround time. Real-time data processing involves continuous input, processing and output of data, with the condition that the time required for processing is as short as possible. This book covers the majority of the existing and evolving open source technology stack for real-time processing and analytics. You will get to know about all the real-time solution aspects, from the source to the presentation to persistence. Through this practical book, you'll be equipped with a clear understanding of how to solve challenges on your own. We'll cover topics such as how to set up components, basic executions, integrations, advanced use cases, alerts, and monitoring. You'll be exposed to the popular tools used in real-time processing today such as Apache Spark, Apache Flink, and Storm. Finally, you will put your knowledge to practical use by implementing all of the techniques in the form of a practical, real-world use case. By the end of this book, you will have a solid understanding of all the aspects of real-time data processing and analytics, and will know how to deploy the solutions in production environments in the best possible manner. Style and Approach In this practical guide to real-time analytics, each chapter begins with a basic high-level concept of the topic, followed by a practical, hands-on implementation of each concept, where you can see the working and execution of it. The book is written in a DIY style, with plenty of practical use cases, well-explained code examples, and relevant screenshots and diagrams.

Handling Qualitative Data

Author : Lyn Richards
Publisher : SAGE
ISBN 13 : 1446242900
Total Pages : 233 pages
Book Rating : 4.4/5 (462 download)

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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.

Data Management Using Stata

Author : Michael N Mitchell
Publisher : Stata Press
ISBN 13 : 9781597183185
Total Pages : 512 pages
Book Rating : 4.1/5 (831 download)

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Book Synopsis Data Management Using Stata by : Michael N Mitchell

Download or read book Data Management Using Stata written by Michael N Mitchell and published by Stata Press. This book was released on 2020-06-25 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.

Data Mining

Author : Ian H. Witten
Publisher : Elsevier
ISBN 13 : 0080890369
Total Pages : 665 pages
Book Rating : 4.0/5 (88 download)

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Book Synopsis Data Mining by : Ian H. Witten

Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Data Management

Author : Margaret E. Henderson
Publisher : Rowman & Littlefield
ISBN 13 : 144226439X
Total Pages : 215 pages
Book Rating : 4.4/5 (422 download)

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Book Synopsis Data Management by : Margaret E. Henderson

Download or read book Data Management written by Margaret E. Henderson and published by Rowman & Littlefield. This book was released on 2016-10-25 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: Libraries organize information and data is information, so it is natural that librarians should help people who need to find, organize, use, or store data. Organizations need evidence for decision making; data provides that evidence. Inventors and creators build upon data collected by others. All around us, people need data. Librarians can help increase the relevance of their library to the research and education mission of their institution by learning more about data and how to manage it. Data Management will guide readers through: Understanding data management basics and best practices. Using the reference interview to help with data management Writing data management plans for grants. Starting and growing a data management service. Finding collaborators inside and outside the library. Collecting and using data in different disciplines.

Practical Guide to Clinical Data Management

Author : Susanne Prokscha
Publisher : CRC Press
ISBN 13 : 1439848319
Total Pages : 296 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Practical Guide to Clinical Data Management by : Susanne Prokscha

Download or read book Practical Guide to Clinical Data Management written by Susanne Prokscha and published by CRC Press. This book was released on 2011-10-26 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then,

Fundamentals and Analytical Applications of Multiway Calibration

Author :
Publisher : Elsevier
ISBN 13 : 0444635378
Total Pages : 612 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Fundamentals and Analytical Applications of Multiway Calibration by :

Download or read book Fundamentals and Analytical Applications of Multiway Calibration written by and published by Elsevier. This book was released on 2015-08-10 with total page 612 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals and Analytical Applications of Multi-Way Calibration presents researchers with a set of effective tools they can use to obtain the maximum information from instrumental data. It includes the most advanced techniques, methods, and algorithms related to multi-way calibration and the ways they can be applied to solve actual analytical problems. This book provides a comprehensive coverage of the main aspects of multi-way analysis, including fundamentals and selected applications of chemometrics that can resolve complex analytical chemistry problems through the use of multi-way calibration. Includes the most advanced techniques, methods, and algorithms related to multi-way calibration and the ways they can be applied to solve actual analytical problems Presents researchers with a set of effective tools they can use to obtain the maximum information from instrumental data Provides comprehensive coverage of the main aspects of multi-way analysis, including fundamentals and selected applications of chemometrics

Practical Data Analysis

Author : Hector Cuesta
Publisher : Packt Publishing Ltd
ISBN 13 : 1785286668
Total Pages : 330 pages
Book Rating : 4.7/5 (852 download)

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Book Synopsis Practical Data Analysis by : Hector Cuesta

Download or read book Practical Data Analysis written by Hector Cuesta and published by Packt Publishing Ltd. This book was released on 2016-09-30 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Data Handling and Analysis

Author : Andrew D. Blann
Publisher : Oxford University Press, USA
ISBN 13 : 0199667918
Total Pages : 205 pages
Book Rating : 4.1/5 (996 download)

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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.

Knowledge Graphs and Big Data Processing

Author : Valentina Janev
Publisher : Springer Nature
ISBN 13 : 3030531996
Total Pages : 212 pages
Book Rating : 4.0/5 (35 download)

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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.

Practical Data Analysis Cookbook

Author : Tomasz Drabas
Publisher : Packt Publishing Ltd
ISBN 13 : 1783558512
Total Pages : 384 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Practical Data Analysis Cookbook by : Tomasz Drabas

Download or read book Practical Data Analysis Cookbook written by Tomasz Drabas and published by Packt Publishing Ltd. This book was released on 2016-04-29 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

Data Collection and Management

Author : Magda Stouthamer-Loeber
Publisher : SAGE Publications, Incorporated
ISBN 13 :
Total Pages : 152 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Data Collection and Management by : Magda Stouthamer-Loeber

Download or read book Data Collection and Management written by Magda Stouthamer-Loeber and published by SAGE Publications, Incorporated. This book was released on 1995-08-08 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tired of a trial-and-error approach to collecting and managing data? Data Collection and Management offers helpful information on managing research projects. By stressing how to use good standards for data collecting and processing, the authors cover such important how-tos as planning research activities; making budgetary decisions and keeping the budget under control; hiring, training, and supervising field interviewing staff; establishing whether interviewers are ready to start interviewing; and ensuring high participant acquisition and retention rates. The book also covers using computerized information systems for tracking data collected and the data management process. Proposal writers, principal investigators, graduate research students, and project coordinators of research requiring large-scale field data collection will find the book to be an indispensable tool.

Practical Data Processing Management

Author : Louis Fried
Publisher : Reston
ISBN 13 :
Total Pages : 360 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Practical Data Processing Management by : Louis Fried

Download or read book Practical Data Processing Management written by Louis Fried and published by Reston. This book was released on 1979 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Predictive Data Mining

Author : Sholom M. Weiss
Publisher : Morgan Kaufmann
ISBN 13 : 9781558604032
Total Pages : 244 pages
Book Rating : 4.6/5 (4 download)

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Book Synopsis Predictive Data Mining by : Sholom M. Weiss

Download or read book Predictive Data Mining written by Sholom M. Weiss and published by Morgan Kaufmann. This book was released on 1998 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first technical guide to provide a complete, generalized road map for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.