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78,889 result(s) for "Quantitative research."
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Health and Social Care Research Methods in Context
This is the first textbook to show how research using a range of qualitative and quantitative methods relates to improving health and social care practice. The book shows how different research approaches are undertaken in practice and the challenges and strengths of different methodologies, thus facilitating students to make informed decisions when choosing which to use in their own research projects. The eleven chapters are each structured around different research methods and include: A brief overview of the research and research question Identification and overview of the research approach and associated methods selected to answer this question The sample and recruitment, including issues and challenges Ethical concerns Practical issues in undertaking the research approach Links between the research process and findings to health and social care values Links to the full research study Further reading The book will be a required reading for all students of social work; social care; nursing; public health and health studies and particularly suitable for those on widening participation courses.
Data analysis and applications. 2, Utilization of results in Europe and other topics
\"This series of books collects a diverse array of work that provides the reader with theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications. Volume 2 begins with an introductory chapter by Gilbert Saporta, a leading expert in the field, who summarizes the developments in data analysis over the last 50 years. The book is then divided into four parts: Part 1 examines (in)dependence relationships, innovation in the Nordic countries, dentistry journals, dependence among growth rates of GDP of V4 countries, emissions mitigation, and five-star ratings; Part 2 investigates access to credit for SMEs, gender-based impacts given Southern Europe's economic crisis, and labor market transition probabilities; Part 3 looks at recruitment at university job-placement offices and the Program for International Student Assessment; and Part 4 examines discriminants, PageRank, and the political spectrum of Germany.\"-- Provided by publisher.
Analysis of Experimental Data in Science and Technology
This textbook presents methods of data analysis and uncertainty estimation based on classical statistics whilst including the use of robust statistics, Monte Carlo modelling, informational criteria, and non-statistical methods. Related computer programs and their creative use are also discussed, without reference to specific packages. The book contains one hundred illustrations and numerous examples using real-world data, from a student lab to the latest scientific results. It will appeal to students, scientists, engineers, metrologists, and everyone interested in processing measurement results.
Applied Modeling Techniques and Data Analysis 1
BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that continues to grow enormously, most notably over the last few decades, following rapid growth within the tech industry, as well as the wide applicability of computational techniques alongside new advances in analytic tools. Modeling enables data analysts to identify relationships, make predictions, and to understand, interpret and visualize the extracted information more strategically. This book includes the most recent advances on this topic, meeting increasing demand from wide circles of the scientific community. Applied Modeling Techniques and Data Analysis 1 is a collective work by a number of leading scientists, analysts, engineers, mathematicians and statisticians, working on the front end of data analysis and modeling applications. The chapters cover a cross section of current concerns and research interests in the above scientific areas. The collected material is divided into appropriate sections to provide the reader with both theoretical and applied information on data analysis methods, models and techniques, along with appropriate applications.
Decisions Over Decimals
Become a confident leader and use data, experience, and intuition to drive your decisions Agile decision making is imperative as you lead in a data-driven world. Amid streams of data and countless meetings, we make hasty decisions, slow decisions, and often no decisions. Uniquely bridging theory and practice, Decisions Over Decimals breaks this pattern by uniting data intelligence with human judgment to get to action — a sharp approach the authors refer to as Quantitative Intuition (QI). QI raises the power of thinking beyond big data without neglecting it and chasing the perfect decision while appreciating that such a thing can never really exist. Successful decision-makers are fierce interrogators. They square critical thinking with open-mindedness by blending information, intuition, and experience. Balancing these elements is at the heart of Decisions Over Decimals. This book is not only designed to be read - but frequently referenced - as you face innumerable decision moments. It is the hands-on manual for confident, accurate decision-making you've been looking for; the rare resource that provides a set of pragmatic leadership tools to accelerate: * Effectively framing the problem for stakeholders * Synthesizing intelligence from incomplete information * Delivering decisions that stick Strike the right balance between information and intuition and lead the smarter way with the real-world guidance found in Decisions Over Decimals.
Literary mathematics : quantitative theory for textual studies
Across the humanities and social sciences, scholars increasingly use quantitative methods to study textual data. Considered together, this research represents an extraordinary event in the long history of textuality. More or less all at once, the corpus has emerged as a major genre of cultural and scientific knowledge. In Literary Mathematics, Michael Gavin grapples with this development, describing how quantitative methods for the study of textual data offer powerful tools for historical inquiry and sometimes unexpected perspectives on theoretical issues of concern to literary studies. Student-friendly and accessible, the book advances this argument through case studies drawn from the Early English Books Online corpus. Gavin shows how a copublication network of printers and authors reveals an uncannily accurate picture of historical periodization; that a vector-space semantic model parses historical concepts in incredibly fine detail; and that a geospatial analysis of early modern discourse offers a surprising panoramic glimpse into the period's notion of world geography. Across these case studies, Gavin challenges readers to consider why corpus-based methods work so effectively and asks whether the successes of formal modeling ought to inspire humanists to reconsider fundamental theoretical assumptions about textuality and meaning. As Gavin reveals, by embracing the expressive power of mathematics, scholars can add new dimensions to digital humanities research and find new connections with the social sciences.