Products related to Homogeneity:
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Quantitative Longitudinal Data Analysis : Research Methods
First published Open Access under a Creative Commons license as What is Quantitative Longitudinal Data Analysis?, this title is now also available as part of the Bloomsbury Research Methods series. Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources.But, to date, many texts on analysing longitudinal social analysis surveys have been written from a statistical, rather than a social science data analysis perspective and they lack adequate coverage of common practical challenges associated with social science data analyses. This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences.The book introduces definitions and terms, explains the relative attractions of such a longitudinal design, and offers an introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution.
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Data Analysis in Qualitative Research : Theorizing with Abductive Analysis
From two experts in the field comes an accessible, how-to guide that will help researchers think more productively about the relation between theory and data at every stage of their work. In Data Analysis in Qualitative Research, Iddo Tavory and Stefan Timmermans provide a how-to guide filled with tricks of the trade for researchers who hope to take excellent qualitative data and transform it into powerful scholarship.In their previous book, Abductive Analysis: Theorizing Qualitative Research, Timmermans and Tavory offered a toolkit for innovative theorizing in the social sciences.In this companion, they go one step further to show how to uncover the surprising revelations that lie waiting in qualitative data—in sociology and beyond. In this book, they lay out a series of tools designed to help both novice and expert scholars see and understand their data in surprising ways.Timmermans and Tavory show researchers how to “stack the deck” of qualitative research in favor of locating surprising findings that may lead to theoretical breakthroughs, whether by engaging with theory, discussing research strategies, or walking the reader through the process of coding data.From beginning to end of a research project, Data Analysis in Qualitative Research helps social scientists pinpoint the most promising paths to take in their approach.
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User Experience Research and Usability of Health Information Technology
Health information technology (HIT) is a critical component of the modern healthcare system.Yet to be effective and safely implemented in healthcare organizations and physicians and patients’ lives, it must be usable and useful.User Experience (UX) research is required throughout the full system design lifecycle of HIT products, which involve a user-centered and human- centered approach.This book discusses UX research frameworks, study designs, methods, data-analysis techniques, and a variety of data collection instruments and tools that can be used to conduct UX research in the healthcare space, all of which involve HIT and digital health.This book is for academics and scholars to be used to design studies for graduate dissertation work, in independent research, or as a textbook for UX/usability courses in health informatics or related health information and communication courses.This book is also useful for UX practitioners because it provides guidance on how to design a user research or usability study and focuses on leveraging a mixed- methods approach, including step-by-step by instructions and best practices for conducting:Field studiesInterviewsFocus groupsDiary studiesSurveysHeuristic evaluation Cognitive walkthrough Think aloudA plethora of standardized surveys and retrospective questionnaires (SUS, Post-study System Usability Questionnaire (PSSUQ)) are also included.UX researchers and healthcare professionals will gain an understanding of how to design a rigorous, yet feasible study that generates useful insights to inform the design of usable HIT.Everything from consent forms to how many participants to include in a usability study has been covered in this book.The author encourages user-centered design (UCD), mixed-methods, and collaboration amongst interdisciplinary teams.Knowledge from many inter-related disciplines, like psychology, technical communication (TC), and human-computer interaction (HCI), together with experiential knowledge from experts is offered throughout the text.
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Market Research and Analysis : Methods, Design and Data
This book provides a comprehensive discussion of market research and analysis, covering key concepts, process descriptions, qualitative and quantitative techniques for market research and data analysis, and application scenarios.Although it is not an academic textbook, it is geared toward business management professionals and graduate students who want to enhance their skills in addressing management decision problems (MDP) and test them for statistical significance.Readers will appreciate the breadth and depth of this subject, market research techniques, and how they are relevant to the business enterprise, whether it is a startup entrepreneurship or an established business organization.This book guides readers on how to conduct market research and solve business challenges.The structure of the book is based on the six steps of the market research process: problem definition, development of an approach to the problem, research design formulation, fieldwork and data collection, data preparation, qualitative and quantitative analysis, statistical test of significance of results, report preparation, and presentation.
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What is the degree of homogeneity?
The degree of homogeneity refers to the level of uniformity or similarity within a group or population. It measures the extent to which the individuals or elements within the group are alike in terms of certain characteristics or attributes. A high degree of homogeneity indicates a high level of similarity, while a low degree of homogeneity indicates a greater diversity or variation within the group. This concept is often used in statistics, sociology, and other fields to analyze and understand the composition and characteristics of a given group.
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Was the degree of homogeneity calculated correctly?
Yes, the degree of homogeneity was calculated correctly. The formula used to calculate homogeneity takes into account the differences between the observed frequencies and the expected frequencies under the null hypothesis. By comparing these values and calculating the chi-square statistic, we can determine the degree of homogeneity in the data.
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Was the degree of homogeneity correctly calculated?
Yes, the degree of homogeneity was correctly calculated. The formula used to calculate homogeneity takes into account the number of categories and the distribution of values within those categories, providing an accurate measure of how similar or different the data points are. By applying this formula to the dataset, the degree of homogeneity was determined accurately.
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How can one check for homogeneity in mathematics?
One can check for homogeneity in mathematics by examining whether a mathematical expression or equation remains unchanged when all its variables are scaled by a common factor. For example, in an equation like ax + by = c, if we multiply both sides of the equation by a constant k, the equation remains unchanged if a and b are both multiplied by k. This property is known as homogeneity. Another way to check for homogeneity is to verify that the dimensions of all terms in an equation are consistent, meaning that they have the same units. If an equation is homogeneous, it means that it is invariant under scaling, which can be a useful property in mathematical analysis and modeling.
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Intelligence Agencies, Technology and Knowledge Production : Data Processing and Information Transfer in Secret Services during the Cold War
This volume examines intelligence services since 1945 in their role as knowledge producers. Intelligence agencies are producers and providers of arcane information.However, little is known about the social, cultural and material dimensions of their knowledge production, processing and distribution.This volume starts from the assumption that during the Cold War, these core activities of information services underwent decisive changes, of which scientization and computerisation are essential.With a focus on the emerging alliances between intelligence agencies, science and (computer) technology, the chapters empirically explore these transformations and are characterised by innovative combinations of intelligence history with theoretical considerations from the history of science and technology and the history of knowledge. At the same time, the book challenges the bipolarity of Cold War history in general and of intelligence history in particular in favour of comparative and transnational perspectives.The focus is not only the Soviet Union and the United States, but also Poland, Turkey, the two German states and Brazil.This approach reveals surprising commonalities across systems: time and again, the expansion and use of intelligence knowledge came up against the limits that resulted from intelligence culture itself.The book enriches our global understanding of knowledge of the state and contributes to a historical framework for the past decade of debates about the societal consequences of intelligence data processing. This book will be of much interest to students of intelligence studies, science and technology studies, security studies and International Relations.
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Handbook of Research on Knowledge and Organization Systems in Library and Information Science
Due to changes in the learning and research environment, changes in the behavior of library users, and unique global disruptions such as the COVID-19 pandemic, libraries have had to adapt and evolve to remain up-to-date and responsive to their users.Thus, libraries are adding new, digital resources and services while maintaining most of the old, traditional resources and services.New areas of research and inquiry in the field of library and information science explore the applications of machine learning, artificial intelligence, and other technologies to better serve and expand the library community.The Handbook of Research on Knowledge and Organization Systems in Library and Information Science examines new technologies and systems and their application and adoption within libraries.This handbook provides a global perspective on current and future trends concerning library and information science.Covering topics such as machine learning, library management, ICTs, blockchain technology, social media, and augmented reality, this book is essential for librarians, library directors, library technicians, media specialists, data specialists, catalogers, information resource officers, administrators, IT consultants and specialists, academicians, and students.
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Quantitative Data Analysis : Doing Social Research to Test Ideas
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.Each chapter includes illustrative examples and a set of exercises that allows readers to test their understanding of the topic.The book, written for graduate students in the social sciences, public health, and education, offers a practical approach to making sociological sense out of a body of quantitative data.The book also will be useful to more experienced researchers who need a readily accessible handbook on quantitative methods. The author has posted stata files, updates and data sets at his website http://tinyurl.com/Treiman-stata-files-data-sets.
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Statistics: A Tool for Social Research and Data Analysis
Extremely student friendly, Healey's STATISTICS: A TOOL FOR SOCIAL RESEARCH AND DATA ANALYSIS, 11e, equips you with a solid understanding of statistical fundamentals and their practical application to current social issues -- no advanced math knowledge required.The text breaks down even the most complex material to help you master key concepts and develop the skills you need as a professional in a social science field -- or simply to become a "statistically literate" consumer of social research.Everyday examples illustrate that statistics are not just abstract mathematical constructs, but they have practical value in government, education, business, media, politics, sports and more.Research examples in every chapter include the same "real data" used by professionals across various fields to make evidence-based decisions.Also available: MindTap digital learning solution.
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What exactly does a specialist in information technology for data and process analysis do?
A specialist in information technology for data and process analysis is responsible for analyzing and interpreting data to identify trends, patterns, and insights that can be used to improve business processes and decision-making. They use various tools and techniques to collect, clean, and analyze data, and then present their findings to stakeholders in a clear and understandable manner. They also work to identify areas for process improvement and develop strategies to optimize workflows and increase efficiency. Overall, their role is to leverage technology and data to drive informed decision-making and improve business operations.
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Is the Levene test for homogeneity of variances the same as one-way ANOVA?
No, the Levene test for homogeneity of variances is a separate statistical test used to assess whether the variances of the groups being compared in an ANOVA are equal. On the other hand, one-way ANOVA is a hypothesis test used to determine whether there are statistically significant differences between the means of three or more independent groups. The Levene test is often conducted before performing an ANOVA to ensure that the assumption of homogeneity of variances is met.
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Is the Levene test for homogeneity of variances the same as the one-way ANOVA?
No, the Levene test for homogeneity of variances is a separate statistical test from the one-way ANOVA. The Levene test is used to determine if the variances of the groups being compared in an ANOVA are equal. It tests the null hypothesis that the variances are equal across all groups. On the other hand, the one-way ANOVA is used to test the null hypothesis that the means of the groups are equal. While both tests are related to comparing groups, they are testing different aspects of the data.
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What prior knowledge does a specialist in information technology for system integration need?
A specialist in information technology for system integration needs a strong foundation in computer science, including knowledge of programming languages, operating systems, and network architecture. They also need to understand database management, cybersecurity, and cloud computing. Additionally, they should have expertise in integrating different software and hardware systems, as well as experience with project management and problem-solving skills. Finally, staying updated with the latest technological advancements and industry trends is crucial for a specialist in information technology for system integration.
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