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Using R for Data Analysis in Social Sciences

A Research Project-Oriented Approach

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.

Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and ...

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 ...

Contemporary Research Methods and Data Analytics in the News Industry

The advent of digital technologies has changed the news and publishing industries drastically. While shrinking newsrooms may be a concern for many, journalists and publishing professionals are working to reorient their skills and capabilities to employ technology for the purpose of better understanding and engaging with their audiences. Contemporary Research Methods and Data Analytics in the News Industry highlights the research behind the innovations and emerging practices being implemented within the journalism industry. This crucial, industry-shattering publication focuses on key topics in social media and video streaming as a new form of media communication as well the application of big data and data analytics for collecting information and drawing conclusions about the current and future state of print and digital news. Due to significant insight surrounding the latest applications and technologies affecting the news industry, this publication is a must-have resource for journalists, analysts, news media professionals, social media strategists, researchers, television news producers, and upper-level students in journalism and media studies. This timely industry resource includes key topics on the changing scope of the news and publishing industries including, but not limited to, big data, broadcast journalism, computational journalism, computer-mediated communication, data scraping, digital media, news media, social media, text mining, and user experience.

Recognize the News Form News stories, like scholarly research articles, have a basic structure—the headline, the lede paragraph, the byline (author) and a writing style. Beyond these basic structural elements, news stories have other ...

Qualitative Research

A Guide to Design and Implementation

"This thoroughly revised and updated classic once again presents aguide to understanding, designing and conducting a qualitativeresearch study. The fourth edition retains the reader-friendly, jargon-free style,making the book accessible to both novice and experiencedresearchers. While the book is practical guide to design andimplementation of a qualitative research study, it also helpsreaders understand the theoretical and philosophical underpinningsof this research paradigm. Drawing on the latest literature as well as both authors'experience with conducting and teaching qualitative research, thefourth edition includes new material on case study research andaction research; discussion of online data sources (video, email,skype); updated discussion of data analysis software packages anduses; new discussion of data analysis strategies, includingnarrative analysis and poetic analysis; and a section on multipleways of presenting qualitative research findings. References,examples, and quotes have all been updated throughout the book"--

No doubt this book will change the way we think about and publish qualitative research." —Leona M. English, head of publications and research, UNESCO Institute of Lifelong Learning, Hamburg

Financial Numeracy in Mathematics Education

Research and Practice

This book presents the important role of mathematics in the teaching of financial education. Through a conceptualization of financial numeracy as a social practice, it focuses on the teaching practices, resources, and needs of secondary mathematics teachers (grades 7-12) to incorporate financial concepts in their classes. The editors and authors bring forth a novel perspective regarding mathematics education in the digital era. By focusing on financial numeracy, a key component of skills required in the digital era, they discuss important issues related to the teaching and learning of mathematics and finance. In contrary to most research in the field of financial education coming from scholars in areas such as business, accounting, management and economics, this book introduces the contribution of researchers from the field of education to the debate. The book appeals to an international audience composed of researchers, stakeholders, policymakers, teachers, and teacher educators.

The book appeals to an international audience composed of researchers, stakeholders, policymakers, teachers, and teacher educators. This book presents the important role of mathematics in the teaching of financial education.

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.