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Analyzing Tabular Data
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Book Synopsis Analyzing Tabular Data by : Nigel Gilbert
Download or read book Analyzing Tabular Data written by Nigel Gilbert and published by Taylor & Francis. This book was released on 2022-02-10 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: First published in 1993, Analyzing Tabular Data is an accessible text introducing a powerful range of analytical methods. Empirical social research almost invariably requires the presentation and analysis of tables, and this book is for those who have little prior knowledge of quantitative analysis or statistics, but who have a practical need to extract the most from their data. The book begins with an introduction to the process of data analysis and the basic structure of cross-tabulations. At the core of the methods described in the text is the loglinear model. This and the logistic model, are explained and their application to causal modelling, to event history analysis, and to social mobility research are described in detail. Each chapter concludes with sample programs to show how analysis on typical datasets can be carried out using either the popular computer packages, SPSS, or the statistical programme, GLIM. The book is packed with examples which apply the methods to social science research. Sociologists, geographers, psychologists, economists, market researchers and those involved in survey research in the fields of planning, evaluation and policy will find the book to be a clear and thorough exposition of methods for the analysis of tabular data.
Book Synopsis Analyzing Tabular Data by : G. Nigel Gilbert
Download or read book Analyzing Tabular Data written by G. Nigel Gilbert and published by . This book was released on 1993 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Python for Data Analysis by : Wes McKinney
Download or read book Python for Data Analysis written by Wes McKinney and published by "O'Reilly Media, Inc.". This book was released on 2017-09-25 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
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 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 Statistical Analysis and Data Display by : Richard M. Heiberger
Download or read book Statistical Analysis and Data Display written by Richard M. Heiberger and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.
Book Synopsis Exploring Data Tables, Trends, and Shapes by : David C. Hoaglin
Download or read book Exploring Data Tables, Trends, and Shapes written by David C. Hoaglin and published by John Wiley & Sons. This book was released on 2011-09-28 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Exploring Data Tables, Trends, and Shapes (EDTTS) was written as a companion volume to the same editors' book, Understanding Robust and Exploratory Data Analysis (UREDA). Whereas UREDA is a collection of exploratory and resistant methods of estimation and display, EDTTS goes a step further, describing multivariate and more complicated techniques . . . I feel that the authors have made a very significant contribution in the area of multivariate nonparametric methods. This book [is] a valuable source of reference to researchers in the area." —Technometrics "This edited volume . . . provides an important theoretical and philosophical extension to the currently popular statistical area of Exploratory Data Analysis, which seeks to reveal structure, or simple descriptions, in data . . . It is . . . an important reference volume which any statistical library should consider seriously." —The Statistician This newly available and affordably priced paperback version of Exploring Data Tables, Trends, and Shapes presents major advances in exploratory data analysis and robust regression methods and explains the techniques, relating them to classical methods. The book addresses the role of exploratory and robust techniques in the overall data-analytic enterprise, and it also presents new methods such as fitting by organized comparisons using the square combining table and identifying extreme cells in a sizable contingency table with probabilistic and exploratory approaches. The book features a chapter on using robust regression in less technical language than available elsewhere. Conceptual support for each technique is also provided.
Book Synopsis Analyzing Neural Time Series Data by : Mike X Cohen
Download or read book Analyzing Neural Time Series Data written by Mike X Cohen and published by MIT Press. This book was released on 2014-01-17 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This book offers a comprehensive guide to the theory and practice of analyzing electrical brain signals. It explains the conceptual, mathematical, and implementational (via Matlab programming) aspects of time-, time-frequency- and synchronization-based analyses of magnetoencephalography (MEG), electroencephalography (EEG), and local field potential (LFP) recordings from humans and nonhuman animals. It is the only book on the topic that covers both the theoretical background and the implementation in language that can be understood by readers without extensive formal training in mathematics, including cognitive scientists, neuroscientists, and psychologists. Readers who go through the book chapter by chapter and implement the examples in Matlab will develop an understanding of why and how analyses are performed, how to interpret results, what the methodological issues are, and how to perform single-subject-level and group-level analyses. Researchers who are familiar with using automated programs to perform advanced analyses will learn what happens when they click the “analyze now” button. The book provides sample data and downloadable Matlab code. Each of the 38 chapters covers one analysis topic, and these topics progress from simple to advanced. Most chapters conclude with exercises that further develop the material covered in the chapter. Many of the methods presented (including convolution, the Fourier transform, and Euler's formula) are fundamental and form the groundwork for other advanced data analysis methods. Readers who master the methods in the book will be well prepared to learn other approaches.
Book Synopsis Development Research in Practice by : Kristoffer Bjärkefur
Download or read book Development Research in Practice written by Kristoffer Bjärkefur and published by World Bank Publications. This book was released on 2021-07-16 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University
Book Synopsis Data Analysis for Social Science by : Elena Llaudet
Download or read book Data Analysis for Social Science written by Elena Llaudet and published by Princeton University Press. This book was released on 2022-11-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--
Book Synopsis Practical Machine Learning for Data Analysis Using Python by : Abdulhamit Subasi
Download or read book Practical Machine Learning for Data Analysis Using Python written by Abdulhamit Subasi and published by Academic Press. This book was released on 2020-06-05 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems. Offers a comprehensive overview of the application of machine learning tools in data analysis across a wide range of subject areas Teaches readers how to apply machine learning techniques to biomedical signals, financial data, and healthcare data Explores important classification and regression algorithms as well as other machine learning techniques Explains how to use Python to handle data extraction, manipulation, and exploration techniques, as well as how to visualize data spread across multiple dimensions and extract useful features
Book Synopsis Tabular Modeling in Microsoft SQL Server Analysis Services by : Marco Russo
Download or read book Tabular Modeling in Microsoft SQL Server Analysis Services written by Marco Russo and published by Microsoft Press. This book was released on 2017-04-12 with total page 1001 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build agile and responsive business intelligence solutions Create a semantic model and analyze data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model. Discover how to: • Determine when a tabular or multidimensional model is right for your project • Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015 • Integrate data from multiple sources into a single, coherent view of company information • Choose a data-modeling technique that meets your organization’s performance and usability requirements • Implement security by establishing administrative and data user roles • Define and implement partitioning strategies to reduce processing time • Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks • Optimize your data model to reduce the memory footprint for VertiPaq • Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models • Select the proper hardware and virtualization configurations • Deploy and manipulate tabular models from C# and PowerShell using AMO and TOM libraries Get code samples, including complete apps, at: https://aka.ms/tabular/downloads About This Book • For BI professionals who are new to SQL Server 2016 Analysis Services or already familiar with previous versions of the product, and who want the best reference for creating and maintaining tabular models. • Assumes basic familiarity with database design and business analytics concepts.
Book Synopsis New Markov Chain Monte Carlo Algorithms for Analyzing Tabular Data by : Philip J. O'Neil
Download or read book New Markov Chain Monte Carlo Algorithms for Analyzing Tabular Data written by Philip J. O'Neil and published by . This book was released on 2000 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Analyzing Data with Power BI and Power Pivot for Excel by : Alberto Ferrari
Download or read book Analyzing Data with Power BI and Power Pivot for Excel written by Alberto Ferrari and published by Microsoft Press. This book was released on 2017-04-28 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness. How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way–like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one! By reading this book, you will: • Gain an understanding of the basics of data modeling, including tables, relationships, and keys • Familiarize yourself with star schemas, snowflakes, and common modeling techniques • Learn the importance of granularity • Discover how to use multiple fact tables, like sales and purchases, in a complex data model • Manage calendar-related calculations by using date tables • Track historical attributes, like previous addresses of customers or manager assignments • Use snapshots to compute quantity on hand • Work with multiple currencies in the most efficient way • Analyze events that have durations, including overlapping durations • Learn what data model you need to answer your specific business questions About This Book • For Excel and Power BI users who want to exploit the full power of their favorite tools • For BI professionals seeking new ideas for modeling data
Book Synopsis Dyadic Data Analysis by : David A. Kenny
Download or read book Dyadic Data Analysis written by David A. Kenny and published by Guilford Publications. This book was released on 2020-11-26 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpersonal phenomena such as attachment, conflict, person perception, learning, and influence have traditionally been studied by examining individuals in isolation, which falls short of capturing their truly interpersonal nature. This book offers state-of-the-art solutions to this age-old problem by presenting methodological and data-analytic approaches useful in investigating processes that take place among dyads: couples, coworkers, parent and child, teacher and student, or doctor and patient, to name just a few. Rich examples from psychology and across the behavioral and social sciences help build the researcher's ability to conceptualize relationship processes; model and test for actor effects, partner effects, and relationship effects; and model and control for the statistical interdependence that can exist between partners. The companion website provides clarifications, elaborations, corrections, and data and files for each chapter.
Book Synopsis Microsoft Office Inside Out (Office 2021 and Microsoft 365) by : Joe Habraken
Download or read book Microsoft Office Inside Out (Office 2021 and Microsoft 365) written by Joe Habraken and published by Microsoft Press. This book was released on 2021-12-22 with total page 1513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conquer Microsoft Office—from the inside out! Dive into the Microsoft Office application suite—and really put its productivity tools and services to work for you! This supremely well-organized reference packs hundreds of timesaving solutions, tips, and workarounds—all you need to make the most of Office's most powerful tools for productivity and decision-making. Renowned Office expert Joe Habraken offers a complete tour of Microsoft Office, with cutting-edge techniques and shortcuts for Word, Excel, PowerPoint, Outlook, Publisher, the 365 Online apps, and more. Discover how experts tackle today's key tasks—and challenge yourself to new levels of mastery. Create amazing content faster with Office's new features, tools, and shortcuts. Share, collaborate with, and secure Office files in the cloud. Organize, edit, and format complex documents with Microsoft Word. Build tables of contents, captions, indexes, and footnotes that automatically update. Efficiently enter and manage data in Excel workbooks, and format it for easy understanding. Build flexible, reliable Excel workbooks with formulas and functions—including XLOOKUP and other enhancements. Integrate data from external sources, including stock and currency data, and Wolfram curated knowledge. Transform data into insight with Pivot Tables and Excel charts — including new recommended charts and the Quick Analysis gallery. Quickly create presentations with PowerPoint themes, Reuse Slides, and Libraries. Build more impactful slides with advanced formatting, SmartArt, animation, transitions, media, and free stock images. Use PowerPoint tools to present more effectively—in person or online via Microsoft Teams. Systematically improve email productivity and security with Outlook. Manage appointments and tasks and quickly plan meetings.
Book Synopsis Contingency Table Analysis by : Maria Kateri
Download or read book Contingency Table Analysis written by Maria Kateri and published by Springer. This book was released on 2014-05-17 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contingency tables arise in diverse fields, including life sciences, education, social and political sciences, notably market research and opinion surveys. Their analysis plays an essential role in gaining insight into structures of the quantities under consideration and in supporting decision making. Combining both theory and applications, this book presents models and methods for the analysis of two- and multidimensional-contingency tables. An excellent reference for advanced undergraduates, graduate students, and practitioners in statistics as well as biosciences, social sciences, education, and economics, the work may also be used as a textbook for a course on categorical data analysis. Prerequisites include basic background on statistical inference and knowledge of statistical software packages.
