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Glossaries | Quantitative Research
Glossary of Key Terms
From Colorado State University: This glossary provides definitions of many of the terms used in the guides to conducting qualitative and quantitative research. The definitions were developed by members of the research methods seminar (E600) taught by Mike Palmquist in the 1990s and 2000s.
Glossary of Quantitative Research Terms
By Professor Detmar Straub of Georgia State University.
Contains basic definitions and examples of presenting data, sampling, probability, confidence intervals, hypothesis testing, paired data, correlation and regression, design of experiments, ANOVA, categorical data, and non-parametric methods. Presented by University of Glasgow.
Selected Books in Specialized Quantitative Methods
Quantitative Finance by
Publication Date: 2009-03-16
A rigorous, yet accessible, introduction to essential topics in mathematical finance
Presented as a course on the topic, Quantitative Finance traces the evolution of financial theory and provides an overview of core topics associated with financial investments. With its thorough explanations and use of real-world examples, this book carefully outlines instructions and techniques for working with essential topics found within quantitative finance including portfolio theory, pricing of derivatives, decision theory, and the empirical behavior of prices.
Quantitative Modeling in Toxicology by
Publication Date: 2010-05-03
Governments around the world are passing laws requiring industry to assess the toxicity of the chemicals and products they produce, but to do so while reducing, refining, or even replacing testing on animals. To meet these requirements, experimental toxicologists and risk assessors are adopting quantitative approaches and computer simulations to study the biological fate and effects of chemicals and drugs.
Quantitative Methods by
Publication Date: 2011-04-26
An accessible introduction to the essential quantitative methods for making valuable business decisions
Quantitative methods-research techniques used to analyze quantitative data-enable professionals to organize and understand numbers and, in turn, to make good decisions. Quantitative Methods: An Introduction for Business Management presents the application of quantitative mathematical modeling to decision making in a business management context and emphasizes not only the role of data in drawing conclusions, but also the pitfalls of undiscerning reliance of software packages that implement standard statistical procedures. With hands-on applications and explanations that are accessible to readers at various levels, the book successfully outlines the necessary tools to make smart and successful business decisions.
What is Quantitative Research?
Quantitative research is the systematic, empirical investigation of phenomena using statistical, mathematical or computational techniques. It is objective. That is, it observes and represents facts without being influenced by personal feelings or opinions.
Dr. Robert Labaree of the University of Southern California Libraries states this about quantitative research: “Quantitative research deals in numbers, logic and the objective, focusing on logic, numbers, and unchanging static data and detailed, convergent reasoning rather than divergent reasoning.”
He goes on to say, “In quantitative research, your goal is to determine the relationship between one thing (an independent variable) and another (a dependent or outcome variable) in a population. Quantitative research designs are either descriptive (subjects usually measured once) or experimental (subjects measured before and after a treatment). A descriptive study establishes only associations between variables. An experiment establishes causality.”
VIDEO: Quantitative vs Qualitative Research
A humorous presentation of qualitative vs quantitative research. The production was created as a midterm submission by students of East Tennessee State University's EDFN 5950 - Methods of Research course.
Published on Mar 6, 2012 | Runtime 4:36 min.
The Xavier University Library (Cincinnati, OH) provides this excellent table that compares the characteristics of Qualitative vs. Quantitative research.
VIDEO: Introduction to Quantitative Research
Dr. Anthony Picciano is a professor in the graduate program in Education Administration and Supervision in the School of Education at Hunter College. He is also on the faculty of the CUNY Graduate Center in the PhD Program in Urban Education and the Program in Integrated Technology and Pedagogy.
This video is one from his introductory lectures. See a list of all his videos here.
Runtime: 2:27 min.
Selected Books on Quantitative Research
Quantitative Data Analysis Using Spss by
Publication Date: 2007-12-01
I remember reading somewhere that for every mathematical formula, included in a book, the sales would be reduced by half. So guess what, there are no formulas, equations or mathematical calculations in this book. This is a practical introduction to quantitative data analysis using the most widely available statistical software – SPSS (Statistical Package for the Social Sciences). The aim is to get students and professionals past that first hurdle of dealing with quantitative data analysis and statistics.
Quantitative Models for Performance Evaluation and Benchmarking by
Publication Date: 2009-03-05
It is difficult to evaluate an organization’s performance when there are multiple inputs and multiple outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. This book introduces DEA as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective.
Applying Quantitative Bias Analysis to Epidemiologic Data by
Publication Date: 2009-05-25
This text provides the first-ever compilation of bias analysis methods for use with epidemiologic data. It guides the reader through the planning stages of bias analysis, including the design of validation studies and the collection of validity data from other sources. Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and classification errors. Subsequent chapters extend these methods to multidimensional bias analysis, probabilistic bias analysis, and multiple bias analysis. The text concludes with a chapter on presentation and interpretation of bias analysis results.
The Graduate Psychometric Test Workbook by
Publication Date: 2011-05-16
Employers want to fill their top management posts with candidates of the highest caliber. Any mistake in their recruitment process can mean wasteful costs in both time and money. Consequently, recruitment to any management post follows a rigorous selection which can include a range of psychometric tests.
Oracle Database Performance and Scalability by
Publication Date: 2011-11-22
A data-driven, fact-based, quantitative text on Oracle performance and scalability
With database concepts and theories clearly explained in Oracle's context, readers quickly learn how to fully leverage Oracle's performance and scalability capabilities at every stage of designing and developing an Oracle-based enterprise application. The book is based on the author's more than ten years of experience working with Oracle, and is filled with dependable, tested, and proven performance optimization techniques.
Selected Journals on Quantitative Research
Journal of Applied Quantitative Methods
A double-blind peer-review scholarly, open access publication in the broad area of quantitative methods whose goal is to identify relevant problems in high need of solutions by encouraging the application of quantitative methods across disciplines
Journal of Quantitative Criminology
Publishes papers that apply quantitative techniques to substantive, methodological, or evaluative concerns relevant to the criminological community. The contents span a broad range of disciplines, drawing on research advances in statistics, sociology, geography, political science, economics, and engineering.
Quantitative Methods for Psychology
Listed in the APUS collection as Tutorials in Quantitative Methods for Psychology. This is the journal's new name. A peer-reviewed electronic journal that publishes articles and tutorials in all areas of quantitative psychology. The mission of the journal is to help both novice and expert researchers acquire methods related to the implementation of experimental paradigms, the description and analysis of data, and the development of quantitative models.
Selected Books on Quantitative Research Data Analysis
Quantitative Data Analysis with SPSS Release 8 for Windows by
Publication Date: 1999-06-17
In this book, we introduce readers to the main techniques of statistical analysis employed by psychologists and sociologists. However, we do not see the book as a standard introduction to statistics. We see the book as distinctively different because we are not concerned to introduce the often complex formulae that underlie the statistical methods covered. Students often find these formulae and the calculations that are associated with them extremely daunting, especially when their background in mathematics is weak. Moreover, in these days of powerful computers and packages of statistical programs, it seems gratuitous to put students through the anxiety of confronting complex calculations when machines can perform the bulk of the work. Indeed, most practitioners employ statistical packages that are run on computers to perform their calculations, so there seems little purpose in treating formulae and their application as a rite de passage for social scientists. Moreover, few students would come to understand fully the rationale for the formulae that they would need to learn. Indeed, we prefer the term ‘quantitative data analysis’ to ‘statistics’ because of the adverse image that the latter term has in the minds of many prospective readers.
Exploratory Data Mining and Data Cleaning by
Publication Date: 2003-05-29
Written for practitioners of data mining, data cleaning and database management.
Presents a technical treatment of data quality including process, metrics, tools and algorithms.
Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge.
Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches.
Uses case studies to illustrate applications in real life scenarios.
Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques.
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