Products related to Quantitative:
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Doing Quantitative Research in Education with IBM SPSS Statistics
This essential guide for education students and researchers explains how to use quantitative methods for analysing educational data using IBM SPSS Statistics. By using datasets from real-life educational research, it demonstrates key statistical techniques that you will need to know, explaining how each procedure can by run on IBM SPSS Statistics.Datasets discussed in the book are downloadable, allowing you to hone your skills as you read. In this third edition, explanations have been updated with figures and screenshots from SPSS version 28, alongside a range of new research examples and updated further reading. Daniel Muijs is Dean of the Faculty of Education and Society at Academica University of Applied Sciences in Amsterdam.
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Quantitative Epidemiology
This book is designed to train graduate students across disciplines within the fields of public health and medicine, with the goal of guiding them in the transition to independent researchers.It focuses on theories, principles, techniques, and methods essential for data processing and quantitative analysis to address medical, health, and behavioral challenges.Students will learn to access to existing data and process their own data, quantify the distribution of a medical or health problem to inform decision making; to identify influential factors of a disease/behavioral problem; and to support health promotion and disease prevention.Concepts, principles, methods and skills are demonstrated with SAS programs, figures and tables generated from real, publicly available data.In addition to various methods for introductory analysis, the following are featured, including 4-dimensional measurement of distribution and geographic mapping, multiple linear and logistic regression, Poissonregression, Cox regression, missing data imputing, and statistical power analysis.
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Understanding Research in Early Childhood Education : Quantitative and Qualitative Methods
This second edition invites readers to be informed consumers of both quantitative and qualitative methods in early childhood research.It offers side-by-side coverage and comparison about the assumptions, questions, purposes, and methods for each, presenting unique perspectives for understanding young children and early care and education programs.The new edition includes updated examples and references as well as a new chapter on equity issues in research.By using this book, students will be able to read, evaluate, and use empirical literature more knowledgeably.These skills are becoming more important as early childhood educators are increasingly expected to use evidence-based research in practice and to participate in collecting and analyzing data to inform their teaching.
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Universities, Employability and Human Development
The book makes a significant contribution to critical higher education studies, specifically to graduate employability research and to capabilities and education research.The book moves beyond the simplistic conception of alleged 'gaps' in graduate skills and 'mismatches' between employers and universities, and instead provides an innovative multi-dimensional and intersectional human capabilities conceptualisation of graduate employability.The book challenges an individualised notion of employability, instead locating employability issues in social and economic conditions, and argues that employability choices cannot be divorced from inequality.Qualitative and quantitative data from multiple case-study universities in South Africa are used to explore the perceptions and experiences of diverse students, lecturers, support officers and employers, regarding what each university is doing, or should be doing, to enhance graduate economic opportunities and contribute to inclusive development.The book will be highly relevant to students, scholars and researchers in the fields of education and sociology, particularly those with an interest in graduate employability.
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What is the difference between quantitative workforce planning and qualitative workforce planning?
Quantitative workforce planning involves using data and metrics to analyze workforce needs, such as forecasting future staffing requirements based on historical trends and projections. This approach focuses on numbers and statistical analysis to make informed decisions about workforce planning. On the other hand, qualitative workforce planning involves a more subjective analysis that considers factors such as employee skills, attitudes, and behaviors. This approach relies on gathering insights through interviews, surveys, and observations to understand the human aspect of workforce planning. Ultimately, combining both quantitative and qualitative approaches can provide a more comprehensive and effective workforce planning strategy.
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What are the advantages and disadvantages of qualitative and quantitative workforce planning?
Qualitative workforce planning allows for a deeper understanding of the human aspect of the workforce, including employee attitudes, motivations, and behaviors. This can provide valuable insights for creating a positive work environment and improving employee satisfaction. However, qualitative data can be subjective and may not always be easily measurable or comparable. On the other hand, quantitative workforce planning provides concrete, measurable data that can be used to make more objective decisions. This can be particularly useful for forecasting future workforce needs and analyzing trends. However, quantitative data may not capture the full complexity of human behavior and can overlook important qualitative factors that impact the workforce. Ultimately, a combination of both qualitative and quantitative workforce planning can provide a more comprehensive understanding of the workforce and help organizations make more informed decisions.
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What are quantitative questions?
Quantitative questions are those that can be answered with numerical data or measurements. These questions often seek to quantify or measure something, such as the frequency, amount, or size of a particular phenomenon. They are commonly used in research and surveys to gather specific data and analyze trends or patterns. Quantitative questions are important for obtaining precise and measurable information that can be used for statistical analysis and drawing conclusions.
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What are quantitative considerations in chemistry?
Quantitative considerations in chemistry involve the measurement and calculation of quantities such as mass, volume, concentration, and moles. These measurements are essential for determining the amount of reactants needed, predicting the amount of products formed, and understanding the stoichiometry of chemical reactions. Quantitative analysis also helps in determining the purity of substances, identifying unknown compounds, and evaluating the efficiency of chemical processes. Overall, quantitative considerations play a crucial role in understanding and applying the principles of chemistry in a practical and quantitative manner.
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Higher Education Policy Analysis Using Quantitative Techniques : Data, Methods and Presentation
This textbook introduces graduate students in education and policy research to data and statistical methods in state-level higher education policy analysis.It also serves as a methodological guide to students, practitioners, and researchers who want a clear approach to conducting higher education policy analysis that involves the use of institutional- and state-level secondary data and quantitative methods ranging from descriptive to advanced statistical techniques. This book is unique in that it introduces readers to various types of data sources and quantitative methods utilized in policy research and in that it demonstrates how results of statistical analyses should be presented to higher education policy makers.It helps to bridge the gap between researchers, policy makers, and practitioners both within education policy and between other fields. Coverage includes identifying pertinent data sources, the creation and management of customized data sets, teaching beginning and advanced statistical methods and analyses, and the presentation of analyses for different audiences (including higher education policy makers).
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Beginning Quantitative Research
This concise text provides a clear and digestible introduction to completing quantitative research.Taking you step-by-step through the process of completing your quantitative research project, it offers guidance on: · Formulating your research question · Completing literature reviews and meta-analysis · Formulating a research design and specifying your target population and data source · Choosing an appropriate method and analysing your findings Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.
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Quantitative Corporate Finance
This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds. Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model.Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance. New to the third edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates.This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.
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Quantitative Investment Analysis
Whether you are a novice investor or an experienced practitioner, Quantitative Investment Analysis, 4th Edition has something for you. Part of the CFA Institute Investment Series, this authoritative guide is relevant the world over and will facilitate your mastery of quantitative methods and their application in todays investment process.This updated edition provides all the statistical tools and latest information you need to be a confident and knowledgeable investor.This edition expands coverage of Machine Learning algorithms and the role of Big Data in an investment context along with capstone chapters in applying these techniques to factor modeling, risk management and backtesting and simulation in investment strategies. The authors go to great lengths to ensure an even treatment of subject matter, consistency of mathematical notation, and continuity of topic coverage that is critical to the learning process.Well suited for motivated individuals who learn on their own, as well as a general reference, this complete resource delivers clear, example-driven coverage of a wide range of quantitative methods.Inside you'll find: Learning outcome statements (LOS) specifying the objective of each chapterA diverse variety of investment-oriented examples both aligned with the LOS and reflecting the realities of todays investment worldA wealth of practice problems, charts, tables, and graphs to clarify and reinforce the concepts and tools of quantitative investment management You can choose to sharpen your skills by furthering your hands-on experience in the Quantitative Investment Analysis Workbook, 4th Edition (sold separately)—an essential guide containing learning outcomes and summary overview sections, along with challenging problems and solutions.
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What is a quantitative performance limitation?
A quantitative performance limitation refers to a specific numerical constraint or restriction that impacts the performance of a system, process, or individual. This limitation is typically measured and expressed in numerical terms, such as a maximum capacity, minimum threshold, or specific numerical target. It can affect various aspects of performance, including speed, capacity, accuracy, and efficiency. Identifying and addressing quantitative performance limitations is important for optimizing performance and achieving desired outcomes.
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Are they qualitative or quantitative data?
Without knowing the specific data in question, it is difficult to determine whether they are qualitative or quantitative. Qualitative data typically involves descriptions, observations, and non-numeric information, while quantitative data involves numerical measurements and counts. If you provide more details about the data, I can help you determine whether it is qualitative or quantitative.
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What does the term quantitative thinking mean?
Quantitative thinking refers to the ability to understand and analyze numerical data in a logical and systematic way. It involves using mathematical and statistical tools to interpret information, make informed decisions, and solve problems. Quantitative thinking helps individuals to critically evaluate data, identify patterns, and draw meaningful conclusions based on evidence and facts. It is an essential skill in various fields such as science, economics, finance, and research.
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What is physics as a quantitative science?
Physics as a quantitative science is the study of the natural world through the use of mathematical and numerical analysis. It seeks to understand and describe the fundamental laws and principles that govern the behavior of matter and energy. By using quantitative methods, such as measurements, calculations, and experiments, physicists are able to make precise predictions and test the validity of their theories. This approach allows for the development of mathematical models that can accurately describe and predict the behavior of physical systems.
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