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Qualitative Research: Data Collection & Data Analysis Techniques (UUM Press)

Qualitative Research: Data Collection & Data Analysis Techniques is especially written for anyone who is interested in doing or learning more about qualitative research methods. The reader-friendly organisation and writing style of the book makes it accessible to everyone-academics,professionals, undergraduates, postgraduates, researchers, and even for those who are just beginning to explore the field of qualitative research. Each chapter provides a clear, contextualized and comprehensive coverage of the main qualitative research methods (interviews, focus groups, observations, diary studies, archival document, and content analysis) and will thus equip readers with a thorough understanding of the steps and skills to undertake qualitative research effectively. Bringing together qualitative research scholars from three different tertiary institutions in the country – Associate Prof Dr. Puvensvary Muthiah, Dr. Radziah Abdul Rahim, Puan Noor Hashima Abd Aziz, and Noor Fadhilah Mat Nayan, from Universiti Utara Malaysia (UUM), Assoc. Prof. Dr. Mastura Badzis from Universiti Pendidikan Sultan Idris (UPSI) and R. Sivabala Naidu from Darulaman Teacher Training Institute, this book addresses some of the most important questions facing students and researchers in qualitative research

Dr. Mastura Badzis from Universiti Pendidikan Sultan Idris (UPSI) and R. Sivabala Naidu from Darulaman Teacher Training Institute, this book addresses some of the most important questions facing students and researchers in qualitative ...

Exploratory Data Analysis in Empirical Research

Proceedings of the 25th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Munich, March 14–16, 2001

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.

This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis.

Adventures in Social Research

Data Analysis Using SPSS 14.0 and 15.0 for Windows

Designed for both introductory and advanced research methods or statistics courses in sociology, political science, social work, criminal justice, and public health departments, Adventures in Social Research is an ideal computer skills and data analysis textbook for any discipline that uses survey methods. New to the Sixth Edition: - Provides a shorter, more condensed version than the Fifth Edition - Illustrates uses of SPSS 14.0 and new GSS data sets - Includes a CD-ROM that contains data sets, Designing Own Survey and comprehensive appendices that include questionnaires, research reports, proposals, survey tips, commands, readings and more - Offers a Web page that features SPSS version update changes for students and instructors

In this thoroughly revised edition, the authors stress active and collaborative learning as students engage in a series of practical investigative exercises.

Research Methodology and Data Analysis Second Edition

This book provides proper direction in doing research especially towards the understanding of research objectives, and research hypotheses. The book also guides in research methodology such as the methods of designing a questionnaire, methods of sampling, methods of data collection and methods of data analysis. The data analysis covers data mining, descriptive analysis, factor analysis, and reliability analysis. Besides this, the book assesses the normality distribution of data since this is crucial in determining the types of statistical analysis to be employed. More importantly, the book offers guide in analysing the correlational effects, causal effects, mediator effects and also the moderator effect among variables in a model.

This book provides proper direction in doing research especially towards the understanding of research objectives, and research hypotheses.

Data Analysis for Social Science and Marketing Research Using Python

A Non Programmer's Guide

The book is written for researchers in social science and marketing field, especially for those with little or no knowledge in computer programming. Data analytics has become part and parcel in the contemporary technologically fast paced world. We have amazing tools and software that allow us to analyse data available in various formats. However, most of the popular paid software and packages for data analysis is not affordable or not even accessible for the students, researchers. This is true in the case of many NGOs and agencies how are involved in community based research in developing countries. We have popular open source platforms and tools such as R and Python for data analysis. This book makes use of Python because of its simplicity, adaptability, broader scope and greater potential in advanced data mining and text mining contexts. We found it as a need to educate and train the researchers from social science and marketing research background, so that they could make use of Python, a promising tool to meet simple to extremely complex data analyses needs free of cost. The learnings from this book will not only help them in doing their conventional data analyses but also enable them to pursue advanced knowledge in machine learning algorithms, text analytics and other new generation techniques with the support of freely accessible open source platforms. Since the objective of the book is to educate the researchers with no programming background, we have made every effort to give hands-on experience in learning some basic coding in Python, which is sufficient for the readers to follow the book. The step-by-step procedure to do various data processing and analysis described in this book will make it easy for the users. Apart from that, we have tried our level best to give explanations on specific codes and how they perform to get us the desired output. We also request you to give you valuable comments and suggestions on the book, via our blog, so that we could improve the same in the upcoming volumes. We commit ourselves to providing explanations to the readers' questions related to the codes and analysis provided in this book. The book specifically deals with data sets of row and column format, as the general format commonly used in social science research, which most of the researchers are familiar with. So we do not work with arrays and dictionaries, except in one or two occasions (only to make you familiar with that) instead prefer to make use of Excel data and pandas data frame. The book consists of thirteen chapters. The first chapter gives an introduction to Python and its relevance and scope in contemporary data analysis contexts. Ch. 2 teaches the basics and Python coding, Ch. 3-7, provide a step-by-step narration of how to enter data, process it, preliminary analysis and data cleaning with the help of Python, Ch.8-9, present data visualizations and narration techniques using Python; Ch.10.demonstrate how Python can use for statistical analysis. The remaining chapters are focusing on giving more real life situations in data analysis and the practical solutions to handle them. The exercises provided in the book are similar to real analysis situations, and that will help the reader for an easy transition to the data analyst jobs. The authors have taken utmost care identifying and providing solutions to all practical difficulties the readers may face while using Python for data analysis purpose. The authors have developed a series of codes and have incorporated them to make data processing and analysis convenient and easy for the researchers. The self-learning materials given in this book will help social science and marketing researchers to deepen their understanding of various steps in data processing and analyses and to gain advanced skills in using Python for this purpose.

This is true in the case of many NGOs and agencies how are involved in community based research in developing countries. We have popular open source platforms and tools such as R and Python for data analysis.

Qualitative Research: Data Collection and Data Analysis Techniques -2nd Edition (UUM Press)

Qualitative Research: Data Collection & Data Analysis Techniques (2nd Edition) has been systematically revised with additional content, more in-depth explanations, and latest references to enhance the knowledge and skills required for those interested in conducting qualitative research. The reader-friendly organisation and writing style of this edition provides guaranteed accessibility to a wide array of readers ranging from established scholars to novice researchers and undergraduates. Each chapter in this edition is set to provide a clear, contextualised and comprehensive coverage of the main qualitative research methods (interviews, focus groups, observations, diary studies, archival document analysis, and content analysis) aimed at equipping readers with a thorough understanding of the design, procedures and skills to effectively undertake qualitative research. At the same time, the authors have anticipated major concerns such as ethical issues that qualitative researchers often face and addressed them in the various chapters. This effort has been made possible through the collaboration involving notable qualitative research scholars from different tertiary institutions – Assoc. Prof. Dr. Puvensvary Muthiah (ELT Consultant), Dr. R. Sivabala Naidu (Taylor’s College), Assoc. Prof. Dr. Mastura Badzis (International Islamic University Malaysia), Dr. Radziah Abdul Rahim (formerly attached to National Defense University of Malaysia), Dr. Noor Fadhilah Mat Nayan (University of Reading), and Assoc. Prof. Noor Hashima Abd Aziz (Universiti Utara Malaysia).

Each chapter in this edition is set to provide a clear, contextualised and comprehensive coverage of the main qualitative research methods (interviews, focus groups, observations, diary studies, archival document analysis, and content ...

Adventures in Social Research

Data Analysis Using IBM® SPSS® Statistics

Providing a practical, hands-on introduction to data conceptualization, measurement and association, this book gives students step-by-step instruction on data analysis using the latest version of SPSS® and the most current General Social Survey data.

In this revised edition, active and collaborative learning will be emphasized as students engage in a series of practical investigative exercises.

Understanding Criminological Research

A Guide to Data Analysis

Criminological research lies at the heart of criminological theory, influences social policy development, as well as informs criminal justice practice. The ability to collect, analyse and present empirical data is a core skill every student of criminology must learn. Written as an engaging step-by-step guide and illustrated by detailed case studies, this book guides the reader in how to analyse criminological data. Key features of the book include: o Guidance on how to identify a research topic, designing a research study, accounting for the role of the researcher and writing up and presenting research findings. o A thorough account of the development of qualitative and quantitative research methodologies and data analysis within the field of criminology. o Relevant and up-to-date case studies, drawn from internationally published criminological research sources. o Clear and accessible chapter content supported by helpful introductions, concise summaries, self-study questions and suggestions for further reading. Understanding Criminological Research: A Guide to Data Analysis in invaluable reading for both undergraduate and postgraduate students in criminology and criminal justice.

Written as an engaging step-by-step guide and illustrated by detailed case studies, this book guides the reader in how to analyse criminological data.

Adventures in Social Research

Data Analysis Using IBM SPSS Statistics

Proud sponsor of the 2019 SAGE Keith Roberts Teaching Innovations Award—enabling graduate students and early career faculty to attend the annual ASA pre-conference teaching and learning workshop. Recipient of the 2018 Cornerstone Author Award! Inspire students to pursue their own adventures in social research with this practical, hands-on introduction to data conceptualization, measurement, and association through active learning. Adventures in Social Research: Data Analysis Using IBM® SPSS® Statistics offers a practical, hands-on introduction to the logic of social science research for students in many disciplines. The fully revised Tenth Edition offers step-by-step instruction on data analysis using the latest version (24.0) of SPSS and current data from the General Social Survey. Organized to parallel most introductory research methods texts, this text starts with an introduction to computerized data analysis and the social research process, then takes readers step-by-step through univariate, bivariate, and multivariate analysis using SPSS Statistics. The range of topics, from beginning to advanced, make Adventures in Social Research appropriate for both undergraduate and graduate courses. For students who are using SPSS for the first time, the free online study site includes video tutorials on basic procedures and operations and includes all SPSS data sets necessary for completing the exercises in the book. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Organized to parallel most introductory research methods texts, this text starts with an introduction to computerized data analysis and the social research process, then takes readers step-by-step through univariate, bivariate, and ...

New Ecology for Education — Communication X Learning

Selected Papers from the HKAECT-AECT 2017 Summer International Research Symposium

This book gathers the best papers from the HKAECT-AECT 2017 Summer International Research Symposium. Revealing the complex interactions between communication and learning, which are represented by the symbol “X” in the title, it provides a platform for knowledge exchange on the new ecology for education in the digital era. It also equips readers to handle complex issues in both communication and education, and clarifies the difference between practitioners and academics in communication and in education.

This book gathers the best papers from the HKAECT-AECT 2017 Summer International Research Symposium.