Computer Programs for Qualitative Data Analysis PDF Download
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Author: Eben Weitzman
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Reference
Languages : en
Pages : 390
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Book Description
Written by qualitative researchers for qualitative researchers, and not presuming extensive computer experience, this user-friendly guide takes a critical look at the wide range of software currently available. The book gives detailed reviews of 24 programs in five major categories: text retrievers, textbase managers, code-and-retrieve programs, code-based theory-builders and conceptual network-builders. In addition, the book provides ratings of over 75 features per program. The authors also offer detailed guidance on the operation of each program, helping the reader to ask key questions about the use of the computer - the nature of the project being undertaken, what time-line analyses are planned and what worksheets are re
Author: Eben Weitzman
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Reference
Languages : en
Pages : 390
Get Book Here
Book Description
Written by qualitative researchers for qualitative researchers, and not presuming extensive computer experience, this user-friendly guide takes a critical look at the wide range of software currently available. The book gives detailed reviews of 24 programs in five major categories: text retrievers, textbase managers, code-and-retrieve programs, code-based theory-builders and conceptual network-builders. In addition, the book provides ratings of over 75 features per program. The authors also offer detailed guidance on the operation of each program, helping the reader to ask key questions about the use of the computer - the nature of the project being undertaken, what time-line analyses are planned and what worksheets are re
Author: Allen Webster
Publisher: Routledge
ISBN: 1136593098
Category : Business & Economics
Languages : en
Pages : 488
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Book Description
Regression analysis is arguably the single most powerful and widely applicable tool in any effective examination of common business issues. Every day, decision-makers face problems that require constructive actions with significant consequences, and regression procedures can prove a meaningful and valuable asset in the decision-making process. This text is designed to help students achieve a full understanding of regression and the many ways it can be used. Taking into consideration current statistical technology, Introductory Regression Analysis focuses on the use and interpretation of software, while also demonstrating the logic, reasoning, and calculations that lie behind any statistical analysis. Furthermore, the text emphasizes the application of regression tools to real-life business concerns. This multilayered, yet pragmatic approach fully equips students to derive the benefit and meaning of a regression analysis. This text is designed to serve in a second undergraduate course in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles of data analysis. Although previous exposure to statistical concepts would prove helpful, all the material needed for an examination of regression analysis is presented here in a clear and complete form.
Author: Nigel Fielding
Publisher: SAGE
ISBN: 9780803974838
Category : Reference
Languages : en
Pages : 218
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Book Description
This work is intended for researchers, academics and students across the social sciences.
Author: Ira H. Bernstein
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Computers
Languages : en
Pages : 464
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Book Description
A textbook for a course teaching students of behavioral sciences how to analyze data using some of the software that has become available for personal computers. Bernstein and Rowe, presumably teachers somewhere, have revived demonstrations as an approach to teaching statistics. They assume students have at least some familiarity with the language and various topics taught in graduate statistics, multivariate analysis, and psychometric theory courses, but not to be experts in any of those fields. c. Book News Inc.
Author: Domenico Talia
Publisher: Elsevier
ISBN: 0128029145
Category : Computers
Languages : en
Pages : 152
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Book Description
Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital data sources available on the Internet using the computing and storage facilities of the cloud. Coverage includes scalable data mining and knowledge discovery techniques together with cloud computing concepts, models, and systems. Specific sections focus on map-reduce and NoSQL models. The book also includes techniques for conducting high-performance distributed analysis of large data on clouds. Finally, the book examines research trends such as Big Data pervasive computing, data-intensive exascale computing, and massive social network analysis. - Introduces data analysis techniques and cloud computing concepts - Describes cloud-based models and systems for Big Data analytics - Provides examples of the state-of-the-art in cloud data analysis - Explains how to develop large-scale data mining applications on clouds - Outlines the main research trends in the area of scalable Big Data analysis
Author: Martin Theus
Publisher: CRC Press
ISBN: 1420011065
Category : Computers
Languages : en
Pages : 293
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Book Description
Interactive Graphics for Data Analysis: Principles and Examples discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets.Fundamentals of Interactive Statistical GraphicsThe first part of the book summarizes principles and methodology, demons
Author: Udo Kelle
Publisher: SAGE Publications Limited
ISBN:
Category : Reference
Languages : en
Pages : 248
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Book Description
Methodological and theoretical issues involved in using computers in qualitative research are examined in this guide. Strategies for computer-assisted qualitative analysis include the discussion of networks of categories; the means of evaluation; and ways of combining analysis techniques.
Author: Rafael A. Irizarry
Publisher: CRC Press
ISBN: 1498775861
Category : Mathematics
Languages : en
Pages : 537
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Book Description
This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Author: Michael R. Berthold
Publisher: Springer
ISBN: 3540486259
Category : Computers
Languages : en
Pages : 515
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Book Description
This second and revised edition contains a detailed introduction to the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues. The following chapters concentrate on machine learning and artificial intelligence, rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on visualization and an advanced overview of IDA processes.
Author: Shen Liu
Publisher: Academic Press
ISBN: 0081006519
Category : Mathematics
Languages : en
Pages : 208
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Book Description
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate
