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Research Methodology and Scientific Writing

This book presents a guide for research methodology and scientific writing covering various elements such as finding research problems, writing research proposals, obtaining funds for research, selecting research designs, searching the literature and review, collection of data and analysis, preparation of thesis, writing research papers for journals, citation and listing of references, preparation of visual materials, oral and poster presentation in conferences, and ethical issues in research . Besides introducing library and its various features in a lucid style, the latest on the use of information technology in retrieving and managing information through various means are also discussed in this book. The book is useful for students, young researchers, and professionals.

This book presents a guide for research methodology and scientific writing covering various elements such as finding research problems, writing research proposals, obtaining funds for research, selecting research designs, searching the ...

Research Methodology in Management and Industrial Engineering

This book deals with methodological issues in the field of management and industrial engineering. It aims to answer the following questions that researchers face every time they look to develop their research: How can we design a research project? What kind of paradigm should we follow? Should we develop a qualitative / phenomenological research or a quantitative / positivistic one? What technics for data collections can we use? Should we use the entire population or a sample? What kind of sampling techniques can we have? This book provides discussion and the exchange of information on principles, strategies, models, techniques, applications and methodological options possible to develop in research in management and industrial engineering. It communicates the latest developments and thinking on the research methodologies subject in the different areas, worldwide. It seeks cultural and geographic diversity in studies highlighting research methodologies that can be used in these different study areas. This book has a special interest in research on important issues that transcend the boundaries of single academic subjects. It presents contributions that challenge the paradigms and assumptions of individual disciplines or functions, with chapters grounded in conceptual and / or empirical literature. The main aim of this book is to provide a channel of communication to disseminate knowledge between academics and researchers, with a special focus on the management and industrial engineering fields. This book can serve as a useful reference for academics, researchers, managers, engineers, and other professionals in related matters with research methodologies. Contributors have identified the theoretical and practical implications of their methodological options to the development and improvement of their different study and research areas.

This book deals with methodological issues in the field of management and industrial engineering.

Research Methodology

A Step-by-Step Guide for Beginners

The Fifth Edition of the bestseller Research Methodology has reimagined, redesigned (now in landscape format), and fully renovated how a textbook can help students achieve success in their methods course or research project.

The Fifth Edition of the bestseller Research Methodology has reimagined, redesigned (now in landscape format), and fully renovated how a textbook can help students achieve success in their methods course or research project.

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 ...

Quantitative Data Analysis

Doing Social Research to Test Ideas

This book is an accessible introduction to quantitative dataanalysis, concentrating on the key issues facing those new toresearch, such as how to decide which statistical procedure issuitable, and how to interpret the subsequent results. Each chapterincludes illustrative examples and a set of exercises that allowsreaders to test their understanding of the topic. The book, writtenfor graduate students in the social sciences, public health, andeducation, offers a practical approach to making sociological senseout of a body of quantitative data. The book also will be useful tomore experienced researchers who need a readily accessible handbookon quantitative methods. The author has posted stata files, updates and data sets athis websitehttp://tinyurl.com/Treiman-stata-files-data-sets.

This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results.

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.

Understanding Clinical Data Analysis

Learning Statistical Principles from Published Clinical Research

This textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings. In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs.

The book will cover the WHY-SOs.

Research Methodology

A Toolkit of Sampling and Data Analysis Techniques for Quantitative Research

Document from the year 2012 in the subject Statistics, grade: -, Monash University Malaysia, Sunway Campus, language: English, comment: Please reference this publication as: Lim, W.M. and Ting, D.H. (2012). Research methodology: a toolkit of sampling and data analysis techniques for quantitative research. GRIN Publishing: Munich, Germany., abstract: Selecting appropriate sampling methods and data analysis techniques for a research study is generally accepted by all researchers in the academia as an imperative component of the research methodology. However, researchers may be encountered with dilemmas when it comes to choosing the most suitable combination of methods to obtain a randomize sample and the best data analysis techniques which are able to project the true state of affairs of the researched phenomenon. This book features a wide range of sampling and data analysis techniques which have been proven to be effectively useful in guiding researchers in the adoption of the most appropriate sampling and data analysis techniques which are in line to accomplish the established research objectives.

This book features a wide range of sampling and data analysis techniques which have been proven to be effectively useful in guiding researchers in the adoption of the most appropriate sampling and data analysis techniques which are in line ...

Data Analysis, Interpretation, and Theory in Literacy Studies Research

A How-To Guide

This research guide addresses the difficulties novice and early career researchers often have with understanding how theory, data analysis and interpretation of findings "hang together" in a well-designed and theorized qualitative research investigation, as well as learning how to draw on such understanding to conduct rigorous data analysis and interpretation of their analytic results. Books that describe data analysis approaches and methods often fail to address the question of how to decide which ones are most appropriate for a particular kind of study, and why they are the best options. This book seeks to clarify these issues in a distinctive way. Chapter authors draw on a successful study they have undertaken and spell out their "problem area," research questions, and theoretical framing, carefully explaining their choices and decisions. They then show in detail how they analyzed their data, and why they took this approach. Finally, they demonstrate how they "translated" or interpreted the results of their analysis, to make them meaningful in research terms. Approaches include interactional sociolinguistics, microethnographic discourse analysis, multimodal analysis, iterative coding, conversation analysis, and multimediated discourse analysis, among others. This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels. Perfect for courses such as: Literacy Research Seminar | Introduction to Qualitative Research | Advanced Research Methods | Studying New Literacies and Media | Research Perspectives in Literacy | Discourse Analysis | Advanced Qualitative Data Analysis | Sociolinguistic Analysis | Classroom Language Research

This book will appeal to beginning researchers and to literacy researchers responsible for teaching qualitative literacy studies research design at undergraduate and graduate levels.

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.