Manage Your Research Data: Data Analysis Software

This book provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems.

This book focuses on tasks that bridge the gap between raw data and statistical analysis. This second edition has been updated throughout to reflect new data management features that have been added over the last 10 years.

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 book will teach you how to take advantage of the JavaScript language to process data provided on the Internet. Much attention is given to the main JavaScript backbone: prototype based objects, and functional capabilities, while common features (loops, etc.) are summarized in a few cheat-sheets. Only operational features are detailed through the coding of several applications -the second and largest part of the book-, on free-access datasets (e.g. World Bank). It includes: cartography (SVG or API's based), data-sheets access (via Ajax or Jsonp), video data and post-synchronization, and animation examples."

"This focuses on models and data that arise from repeated observations of a cross-section of individuals, households or companies. These models have found important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also describes substantive applications from across the social sciences, showing the breadth and scope that these models enjoy. The applications are enhanced by real-world data sets and software programs in SAS and Stata."

"This text invites readers to learn how to use qualitative data analysis software in the context of doing their research project. The reader follows basic steps for creating and conducting a real project with real data, using QSR NVivo."

"Now updated to cover latest versions and featuring instructions for both Mac and Windows users, this book is still the go-to source of support for getting to grips with qualitative data analysis using ATLAS.ti. With over twenty years of experience using, developing, and teaching ATLAS.ti, Susanne Friese is the perfect data analysis tour guide. Aware of common challenges and sticking points, she eases readers from readying and organizing data into coding and querying it, providing not only tips on how to prepare for analysis, but also the tools and technical know-how needed to observe, examine, and discuss data. Placing quick software 'skills training' tutorials alongside different stages of the data analysis process, she gives readers the opportunity to integrate software training with their actual analysis."

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Shows readers how to organize, manage and analyze data from research projects so as to gain the benefits of software use. This title illustrates how electronic projects need to be articulated and organized. It uses case studies and examples - divided in to 'Simple Cases', 'Complex Cases' and 'Compound Complex Cases'."

Providing students and researchers with a guide to systematic analysis, with an emphasis on using software, this is a hands-on introduction to the central steps involved with qualitative analysis.

"This book shows students how to recode data, combine data from different sources, document data, and import data from statistical packages other than R. It explores both qualitative and quantitative data and is packed with a range of supportive learning features such as code examples, overview boxes, images, tables, and diagrams."