Handbook Of Data Analysis
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Handbook Of Data Analysis
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Author : Melissa A Hardy
language : en
Publisher: SAGE
Release Date : 2009-06-17
Handbook Of Data Analysis written by Melissa A Hardy and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-17 with Social Science categories.
′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
Handbook Of Statistical Analysis And Data Mining Applications
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Author : Ken Yale
language : en
Publisher: Elsevier
Release Date : 2017-11-09
Handbook Of Statistical Analysis And Data Mining Applications written by Ken Yale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Mathematics categories.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
The Data Analysis Handbook
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Author : I.E. Frank
language : en
Publisher: Elsevier
Release Date : 1994-09-30
The Data Analysis Handbook written by I.E. Frank and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-09-30 with Education categories.
Analyzing observed or measured data is an important step in applied sciences. The recent increase in computer capacity has resulted in a revolution both in data collection and data analysis. An increasing number of scientists, researchers and students are venturing into statistical data analysis; hence the need for more guidance in this field, which was previously dominated mainly by statisticians.This handbook fills the gap in the range of textbooks on data analysis. Written in a dictionary format, it will serve as a comprehensive reference book in a rapidly growing field. However, this book is more structured than an ordinary dictionary, where each entry is a separate, self-contained entity. The authors provide not only definitions and short descriptions, but also offer an overview of the different topics. Therefore, the handbook can also be used as a companion to textbooks for undergraduate or graduate courses.1700 entries are given in alphabetical order grouped into 20 topics and each topic is organized in a hierarchical fashion. Additional specific entries on a topic can be easily found by following the cross-references in a top-down manner. Several figures and tables are provided to enhance the comprehension of the topics and a list of acronyms helps to locate the full terminologies. The bibliography offers suggestions for further reading.
Handbook Of Data Analysis
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Author : Melissa A Hardy
language : en
Publisher: SAGE
Release Date : 2004-04-21
Handbook Of Data Analysis written by Melissa A Hardy and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-21 with Social Science categories.
This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond. Diagrams and tables are used effectively throughout the text and snippets of sample code provide useful additions to chapters for those of us who are less familiar with statistical software packages. Where equations are used to they are explained and documented with careful explanation of statistical notation. Each of the chapters in the book references a representative range of key authors and seminal texts, making it an ideal springboard for further and more advanced reading... the book provides an excellent reference of quantitative methodology and would provide a very useful addition to the shelves of researches and university libraries. - Environment and Planning This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. However, the book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis. `The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University `With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. While quantitative methods are treated, from basic statistics through the general linear model and beyond, qualitative methods are by no means neglected. Indeed, a unique feature of this volume is the careful integration of quantitative and qualitative approaches. Undoubtedly, this integration succeeds because of the research strengths of the editors, leading social researchers who themselves employ both quantitative and qualitative methods′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa and Editor of the SAGE `Quantitative Applications in the Social Sciences′ series `This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey
The Sage Handbook Of Qualitative Data Analysis
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Author : Uwe Flick
language : en
Publisher: SAGE
Release Date : 2013-12-18
The Sage Handbook Of Qualitative Data Analysis written by Uwe Flick and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-18 with Social Science categories.
The wide range of approaches to data analysis in qualitative research can seem daunting even for experienced researchers. This handbook is the first to provide a state-of-the art overview of the whole field of QDA; from general analytic strategies used in qualitative research, to approaches specific to particular types of qualitative data, including talk, text, sounds, images and virtual data. The handbook includes chapters on traditional analytic strategies such as grounded theory, content analysis, hermeneutics, phenomenology and narrative analysis, as well as coverage of newer trends like mixed methods, reanalysis and meta-analysis. Practical aspects such as sampling, transcription, working collaboratively, writing and implementation are given close attention, as are theory and theorization, reflexivity, and ethics. Written by a team of experts in qualitative research from around the world, this handbook is an essential compendium for all qualitative researchers and students across the social sciences.
Hands On Data Analysis With Pandas
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Author : Stefanie Molin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-29
Hands On Data Analysis With Pandas written by Stefanie Molin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-29 with Computers categories.
Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasks Key Features Perform efficient data analysis and manipulation tasks using pandas 1.x Apply pandas to different real-world domains with the help of step-by-step examples Make the most of pandas as an effective data exploration tool Book DescriptionExtracting valuable business insights is no longer a ‘nice-to-have’, but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time. This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making – valuable knowledge that can be applied across multiple domains.What you will learn Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Solve common data representation and analysis problems using pandas Build Python scripts, modules, and packages for reusable analysis code Who this book is for This book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress. You’ll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.
A Handbook For Data Analysis In The Behaviorial Sciences
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Author : Gideon Keren
language : en
Publisher: Psychology Press
Release Date : 2014-01-14
A Handbook For Data Analysis In The Behaviorial Sciences written by Gideon Keren and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Psychology categories.
Statistical methodology is often conceived by social scientists in a technical manner; they use it for support rather than for illumination. This two-volume set attempts to provide some partial remedy to the problems that have led to this state of affairs. Both traditional issues, such as analysis of variance and the general linear model, as well as more novel methods like exploratory data analysis, are included. The editors aim to provide an updated survey on different aspects of empirical research and data analysis, facilitate the understanding of the internal logic underlying different methods, and provide novel and broader perspectives beyond what is usually covered in traditional curricula.
Statistical Analysis Handbook
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Author : Dr Michael John de Smith
language : en
Publisher: The Winchelsea Press
Release Date :
Statistical Analysis Handbook written by Dr Michael John de Smith and has been published by The Winchelsea Press this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
A Comprehensive Handbook of Statistical Concepts, Techniques and Software Tools.
The Handbook Of Creative Data Analysis
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Author : Helen Kara
language : en
Publisher: Policy Press
Release Date : 2024-09-11
The Handbook Of Creative Data Analysis written by Helen Kara and has been published by Policy Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Social Science categories.
Creative research methods for data generation have expanded over recent decades and researchers are eager to take a creative approach to data analysis. It is challenging to bring creativity into data analysis while retaining a systematic, rigorous and ethical approach. Written by experts in the field, this handbook addresses these challenges. The chapters adapt analytical techniques in creative ways for novice and expert researchers. Existing and novel methods from analysis of quantitative data to embodied, performative, visual, written, arts-based and collaborative analysis are featured with transferable case examples across disciplines. This collection offers a definitive practical guide to creative data analysis.
Handbook Of Data Visualization
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Author : Chun-houh Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-18
Handbook Of Data Visualization written by Chun-houh Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-18 with Computers categories.
Visualizing the data is an essential part of any data analysis. Modern computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. This book gives an overview of modern data visualization methods, both in theory and practice. It details modern graphical tools such as mosaic plots, parallel coordinate plots, and linked views. Coverage also examines graphical methodology for particular areas of statistics, for example Bayesian analysis, genomic data and cluster analysis, as well software for graphics.