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 is an advanced undergraduate - or postgraduate - level text designed for courses in research methods and intermediate quantitative methods offered in departments of psychology, education, sociology and communication. Equally emphasizing the collection and analysis of research data, students should be able to plan an original study, collect and analyze data and report the results of the study in a professional manner.
This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods. Highly practical in nature, the book guides you, step-by-step, through the research process and is underpinned by SPSS screenshots, diagrams and examples throughout.
Research Basics: Design to Data Analysis in Six Steps offers a fresh and creative approach to the research process based on author James V. Spickard’s decades of teaching experience. Using an intuitive six-step model, readers learn how to craft a research question and then identify a logical process for answering it. Conversational writing and multi-disciplinary examples illuminate the model’s simplicity and power, effectively connecting the “hows” and “whys” behind social science research. Students using this book will learn how to turn their research questions into results.
Research Methods: Information, Systems, and Contexts, Second Edition, presents up-to-date guidance on how to teach research methods to graduate students and professionals working in information management, information science, librarianship, archives, and records and information systems. It provides a coherent and precise account of current research themes and structures, giving students guidance, appreciation of the scope of research paradigms, and the consequences of specific courses of action. Each of these valuable sections will help users determine the relevance of particular approaches to their own questions. The book presents academics who teach research and information professionals who carry out research with new resources and guidance on lesser-known research paradigms. - Provides up-to-date knowledge of research methods and their applications - Provides a coherent and precise account of current research themes and structures through chapters written by authors who are experts in their fields - Helps students and researchers understand the range of quantitative and qualitative approaches available for research, as well as how to make practical use of them - Provides many illustrations from projects in which authors have been involved, to enhance understanding - Emphasises the nexus between formulation of research question and choice of research methodology - Enables new researchers to understand the implications of their planning decisions
This slim volume is one of a number of excellent guides published as part of Oxford's "Pocket Guide to Social Work Research Methods" series. Compact but comprehensive, it provides a thorough introduction to one of the fastest-growing genres of research in the social work field today: secondary data analysis. After an all-too-brief summary of what constitutes this genre and a balanced analysis of its advantages and disadvantages, Vartanian (Bryn Mawr) provides guidelines for those considering the feasibility and appropriateness of using secondary data in their work. He then offers extensive summaries of 29 of the most commonly used secondary data sets. For all of the data sets, he provides a full and complete description, including key characteristics and where and how to access them. He also provides, most valuably, citations to examples of how researchers have recently used them in their empirical work. Rather redundantly, a similar package of information appears in appendixes at the end of the book. This is an admirable contribution whose only detractions are the rather random and poorly identified screenshots and other "pictures" interspersed throughout the text. Those seriously considering using secondary data analysis in their research should find this book immensely beneficial. Summing Up: Highly recommended. Graduate students and faculty/researchers. Graduate Students; Researchers/Faculty. Reviewed by J. C. Altman.
One central and enduring image of the social science researcher is of an individual who commits a great deal of time to collecting original, primary data from a field of enquiry. This approach is often underpinned by a sincerely held belief that key research questions can only be explored by the collection of ever new, and ever greater amounts of data, or that already existing data are insufficient for researchers to test their ideas. Yet such an approach to social science research can be problematic not least because the collection of primary data can be an expensive, time-consuming, and even wasteful approach to social enquiry. Secondary analysis can serve many purposes, as well as being a valid approach in its own right. However, despite its widespread application, secondary analysis is often undervalued or perceived to be the preserve of only those interested in the re-use of large-scale survey data. Highlighting both the theory and practice of secondary analysis and the use of secondary sources, this collection considers the nature of secondary analysis as a research tool; reflects on the definitional debates surrounding terms such as secondary analysis, data re-use and restudies; illustrates how secondary analysis is used in social science research; and finally reviews the practical, methodological and ethical aspects of secondary analysis. Volume One: Using Secondary Sources and Secondary Analysis Volume Two: Quantitative Approaches to Secondary Analysis Volume Three: Qualitative Data and Research in Secondary Analysis Volume Four: Ethical, Methodological and Practical Issues in Secondary Analysis
This introductory textbook presents research methods and data analysis tools in non-technical language. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in QDA Miner Lite and IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods and surveys; statistical methods, including hypothesis testing, regression, cluster and factor analysis; and reporting. The intended audience is business and social science students learning scientific research methods, however, given its business context, the book will be equally useful for decision-makers in businesses and organizations.
Whilst the ‘health sciences’ are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences – and students are expected increasingly to do both. Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research – critical numbers, critical appraisal of existing research, and conducting new research – this accessible textbook introduces: Descriptive statistics Measures of association for categorical and continuous outcomes Confounding, effect modification, mediation and causal inference Critical appraisal Searching the literature Randomised controlled trials Cohort studies Case-control studies Research ethics and data management Dissemination and publication Linear regression for continuous outcomes Logistic regression for categorical outcomes. A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book’s exercises and activities. Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences.
