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Understanding Research Methods: An Overview of the Essentials (7th edition)
by Mildred L. PattenTopics include Intro to Research Methods, Reviewing Literature, Sampling, Instrumentation, Experimental Design, Understanding Statistics, Effect Size and Meta-Analysis, Qualitative Research, and Preparing Research Reports.
Understanding Research Methods in Psychology
by Jennie Brooks JamisonThis book has three purposes. One purpose is to help students see that there are many options available to researchers for investigating behavior and that each method has a specific goal. The second purpose is to introduce students to qualitative research methods: interviewing, observation, and case studies. International Baccalaureate (IB) students taking the Higher Level (HL) course sit for Paper 3, a section of the exam about qualitative research. I weave headings throughout the chapters on qualitative research that correspond to Paper 3 learning outcomes. These IB learning outcomes are relevant for any psychology student. The third purpose is to teach students how to design a simple experiment and analyze the data. Students taking the International Baccalaureate and/or Advanced Placement exams in psychology will find what they need in this book. Research methods are probably the most difficult part of these exams. Introductory texts do not usually provide enough depth, while the typical college-level research methods books are too complicated, sometimes even for a college student's first experience with methodology.
Understanding Risk: The Theory and Practice of Financial Risk Management (Chapman and Hall/CRC Financial Mathematics Series)
by David MurphySound risk management often involves a combination of both mathematical and practical aspects. Taking this into account, Understanding Risk: The Theory and Practice of Financial Risk Management explains how to understand financial risk and how the severity and frequency of losses can be controlled. It combines a quantitative approach with a
Understanding Statistical Analysis and Modeling
by Robert H. BruhlUnderstanding Statistical Analysis and Modeling is for readers in the social, behavioral, or managerial sciences mathematics to understand the logic of statistical analysis. Robert Bruhl covers all the basic methods of descriptive and inferential statistics in an accessible manner by way of asking and answering research questions. Concepts are discussed in the context of a specific research project and the book includes probability theory as the basis for understanding statistical inference. Instructions on using SPSS® are included so that readers focus on interpreting statistical analysis rather than calculations. Tables are used, rather than formulas, to describe the various calculations involved with statistical analysis and the exercises in the book are intended to encourage students to formulate and execute their own empirical investigations.
Understanding Statistical Analysis and Modeling
by Robert H. BruhlUnderstanding Statistical Analysis and Modeling is for readers in the social, behavioral, or managerial sciences mathematics to understand the logic of statistical analysis. Robert Bruhl covers all the basic methods of descriptive and inferential statistics in an accessible manner by way of asking and answering research questions. Concepts are discussed in the context of a specific research project and the book includes probability theory as the basis for understanding statistical inference. Instructions on using SPSS® are included so that readers focus on interpreting statistical analysis rather than calculations. Tables are used, rather than formulas, to describe the various calculations involved with statistical analysis and the exercises in the book are intended to encourage students to formulate and execute their own empirical investigations.
Understanding Statistical Error
by Marek GierlinskiThis accessible introductory textbook provides a straightforward, practical explanation of how statistical analysis and error measurements should be applied in biological research. Understanding Statistical Error - A Primer for Biologists: Introduces the essential topic of error analysis to biologists Contains mathematics at a level that all biologists can grasp Presents the formulas required to calculate each confidence interval for use in practice Is based on a successful series of lectures from the author's established course Assuming no prior knowledge of statistics, this book covers the central topics needed for efficient data analysis, ranging from probability distributions, statistical estimators, confidence intervals, error propagation and uncertainties in linear regression, to advice on how to use error bars in graphs properly. Using simple mathematics, all these topics are carefully explained and illustrated with figures and worked examples. The emphasis throughout is on visual representation and on helping the reader to approach the analysis of experimental data with confidence. This useful guide explains how to evaluate uncertainties of key parameters, such as the mean, median, proportion and correlation coefficient. Crucially, the reader will also learn why confidence intervals are important and how they compare against other measures of uncertainty. Understanding Statistical Error - A Primer for Biologists can be used both by students and researchers to deepen their knowledge and find practical formulae to carry out error analysis calculations. It is a valuable guide for students, experimental biologists and professional researchers in biology, biostatistics, computational biology, cell and molecular biology, ecology, biological chemistry, drug discovery, biophysics, as well as wider subjects within life sciences and any field where error analysis is required.
Understanding Statistics
by Bruce J. ChalmerIntroducing undergraduates to the vital concepts of statistics, this superb textbook allows instructors to include as much—or as little—mathematical detail as may be suitable for their students. Featuring Statpal statistical software for the IBM PC®, the book contains study questions that help solidify students’ understanding of the material and prepare them for the next group of concepts. Many of the exercises, labeled “Statpal exercises,” are especially written for the Statpal statistical package. Understanding Statistics begins with the basic concepts of statistical inference … presents normal and binomial distributions, general techniques of interval estimation and hypothesis testing, and applications of these techniques to inferences about a single population mean and proportions … and covers inferences about group differences, including parametric and nonparametric approaches to the two-group case, and the one-way ANOVA and its nonparametric analogue. In addition, this volume considers relationships between two variables, including the correlation co-efficient, Spearman’s rho, and Kendall’s tau ... surveys basic regression methods, including simple, multiple, and stepwise ... and discusses the analysis of variance of factorial designs, the concept of interaction, and the analysis of categorical data using the chi-square test. Complete with tables and drawings plus appendices that furnish instructions for using Statpal software, information on advanced topics, and much more, Understanding Statistics is an ideal text for undergraduate survey courses on statistical methods as well as for courses in economics, psychology, sociology, education, business administration, and others that require basic statistics.
Understanding Statistics and Experimental Design: How to Not Lie with Statistics (Learning Materials in Biosciences)
by Michael H. Herzog Gregory Francis Aaron ClarkeThis open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Understanding Statistics for the Social Sciences with IBM SPSS
by Robert HoModern statistical software provides the ability to compute statistics in a timely, orderly fashion. This introductory statistics textbook presents clear explanations of basic statistical concepts and introduces students to the IBM SPSS program to demonstrate how to conduct statistical analyses via the popular point-and-click and the "syntax file" methods. The focal point is to show students how easy it is to analyse data using SPSS once they have learned the basics. Provides clear explanation of basic statistical concepts that provides the foundation for the beginner students’ statistical journey. Introduces the SPSS software program. Gives clear explanation of the purpose of specific statistical procedures (e.g., frequency distributions, measures of central tendencies, measures of variability, etc.). Avoids the conventional cookbook approach that contributes very little to students’ understanding of the rationale of how the correct results were obtained. The advantage of learning the IBM SPSS software package at the introductory class level is that most social sciences students will employ this program in their later years of study. This is because SPSS is one of the most popular of the many statistical packages currently available. Learning how to use this program at the very start not only familiarizes students with the utility of this program but also provides them with the experience to employ the program to conduct more complex analyses in their later years.
Understanding Statistics in the Behavioral Sciences
by Roger Bakeman Byron F. RobinsonUnderstanding Statistics in the Behavioral Sciences is designed to help readers understand research reports, analyze data, and familiarize themselves with the conceptual underpinnings of statistical analyses used in behavioral science literature. The authors review statistics in a way that is intended to reduce anxiety for students who feel intimidated by statistics. Conceptual underpinnings and practical applications are stressed, whereas algebraic derivations and complex formulas are reduced. New ideas are presented in the context of a few recurring examples, which allows readers to focus more on the new statistical concepts than on the details of different studies.The authors' selection and organization of topics is slightly different from the ordinary introductory textbook. It is motivated by the needs of a behavioral science student, or someone in clinical practice, rather than by formal, mathematical properties. The book begins with hypothesis testing and then considers how hypothesis testing is used in conjunction with statistical designs and tests to answer research questions. In addition, this book treats analysis of variance as another application of multiple regression. With this integrated, unified approach, students simultaneously learn about multiple regression and how to analyze data associated with basic analysis of variance and covariance designs. Students confront fewer topics but those they do encounter possess considerable more power, generality, and practical importance. This integrated approach helps to simplify topics that often cause confusion.Understanding Statistics in the Behavioral Sciences features:*Computer-based exercises, many of which rely on spreadsheets, help the reader perform statistical analyses and compare and verify the results using either SPSS or SAS. These exercises also provide an opportunity to explore definitional formulas by altering raw data or terms within a formula and immediately see the consequences thus providing a deeper understanding of the basic concepts.*Key terms and symbols are boxed when first introduced and repeated in a glossary to make them easier to find at review time.*Numerous tables and graphs, including spreadsheet printouts and figures, help students visualize the most critical concepts.This book is intended as a text for introductory behavioral science statistics. It will appeal to instructors who want a relatively brief text. The book's active approach to learning, works well both in the classroom and for individual self-study.
Understanding Statistics in the Behavioral Sciences (Tenth Edition)
by Robert R. Pagano<p>Based on over 30 years of successful teaching experience in this course, Robert Pagano's introductory text takes an intuitive, concepts-based approach to descriptive and inferential statistics. He uses the sign test to introduce inferential statistics, empirically derived sampling distributions, many visual aids, and lots of interesting examples to promote reader understanding. <p>One of the hallmarks of this text is the positive feedback from users--even those not mathematically inclined praise the text for its clarity, detailed presentation, and use of humor to help make concepts accessible and memorable. Thorough explanations precede the introduction of every formula, and the exercises that immediately follow include a step-by-step model that lets readers compare their work against fully solved examples. This combination makes the text perfect for anyone building their foundation of knowledge for analyzing statistics in psychology or other social and behavioral sciences.</p>
Understanding Statistics in the Behavioural Sciences (9th edition)
by Robert R. PaganoBased on over 30 years of successful teaching experience in this course, Robert Pagano's introductory text takes an intuitive, concepts-based approach to descriptive and inferential statistics. He uses the sign test to introduce inferential statistics, empirically derived sampling distributions, many visual aids and lots of interesting examples to promote student understanding. One of the hallmarks of this text is the positive feedback from students-even students who are not mathematically inclined praise the text for its clarity, detailed presentation, and use of humor to help make concepts accessible and memorable. Thorough explanations precede the introduction of every formula-and the exercises that immediately follow include a step-by-step model that lets students compare their work against fully solved examples. This combination makes the text perfect for students taking their first statistics course in psychology or other social and behavioral sciences.
Understanding Statistics Using R
by Randall Schumacker Sara TomekThis book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials. The book contains R script programs to demonstrate important topics and concepts covered in a statistics course, including probability, random sampling, population distribution types, role of the Central Limit Theorem, creation of sampling distributions for statistics, and more. The chapters contain T/F quizzes to test basic knowledge of the topics covered. In addition, the book chapters contain numerous exercises with answers or solutions to the exercises provided. The chapter exercises reinforce an understanding of the statistical concepts presented in the chapters. An instructor can select any of the supplemental materials to enhance lectures and/or provide additional coverage of concepts and topics in their statistics book. This book uses the R statistical package which contains an extensive library of functions. The R software is free and easily downloaded and installed. The R programs are run in the R Studio software which is a graphical user interface for Windows. The R Studio software makes accessing R programs, viewing output from the exercises, and graphical displays easier to manage. The first chapter of the book covers the fundamentals of the R statistical package. This includes installation of R and R Studio, accessing R packages and libraries of functions. The chapter also covers how to access manuals and technical documentation, as well as, basic R commands used in the R script programs in the chapters. This chapter is important for the instructor to master so that the software can be installed and the R script programs run. The R software is free so students can also install the software and run the R script programs in the chapters. Teachers and students can run the R software on university computers, at home, or on laptop computers making it more available than many commercial software packages.
Understanding Structural Equation Modeling: A Manual for Researchers (Synthesis Lectures on Mathematics & Statistics)
by J.P. Verma Priyam VermaThis book presents a comprehensive overview of Structural Equation Modeling and how it can be applied to address research issues in different disciplines. The authors employ a ‘simple to complex’ approach. The book reviews topics such as variance, covariance, correlation, multiple regression, mediation, moderation, path analysis, and confirmatory factor analysis. The authors then discuss the initial steps for performing structural equation modeling, including model specification, model identification, model estimation, model testing, and model modification. The book includes an introduction to the IBM SPSS and IBM SPSS Amos software. The authors the explain how this software can be utilized for developing measurement, structural models, and SEM models. The book provides conceptual clarity in understanding the models and discusses practical approaches to solving them. The authors also highlight how these techniques can be applied to various disciplines, including psychology, education, sociology, business, medicine, political science, and biological sciences.
Understanding Survey Methodology: Sociological Theory and Applications (Frontiers in Sociology and Social Research #4)
by Philip S. BrennerThis volume ambitiously applies sociological theory to create an understanding of aspects of survey methodology. It focuses on the interplay between sociology and survey methodology: what sociological theory and approaches can offer to survey research and vice versa. The volume starts with a focus on direct connections between sociological theories and their applications in survey research. It further presents cutting-edge, original research that applies the “sociological imagination” to substantive concerns important to sociologists, survey methodologists, and social scientists and includes issues such as health, immigration, race/ethnicity, gender and sexuality, and criminal justice.
Understanding Test and Exam Results Statistically
by Kaycheng SohThis book shares the goal of the classic text How to Lie with Statistics, namely, preventing and correcting statistical misconceptions that are common among practitioners, though its focus is on the educational context. It illustrates and discusses the essentials of educational statistics that will help educational practitioners to do this part of their job properly, i. e. , without making conceptual mistakes. The examples are cast in the school/classroom contexts, based on realistic rather than theoretical examples.
Understanding the Analytic Hierarchy Process (Chapman & Hall/CRC Series in Operations Research)
by Konrad KulakowskiThe aim of this book is to provide the reader with a critical guide to AHP. In this book, the AHP method is considered primarily as a mathematical technique supporting the decision-making process. This method provides a convenient and versatile framework for modelling multi-criteria decision problems, evaluating alternatives and deriving final priorities. Rather than imposing a correct decision, AHP allows the user to create a ranking of alternatives, then choose the one which is the best (or among the best). At the core of AHP is a pairwise comparisons (PC) method. This is an old technique known in various forms since at least the Middle Ages.
Understanding the Context of Cognitive Aging: Mexico and the United States
by Jacqueline L. Angel Mariana López Ortega Luis Miguel Gutiérrez RobledoThis book provides a bi-national portrait of dementia in the rapidly aging Mexican-origin population in Mexico and the United States. It provides a comprehensive overview of critical conceptual and methodological issues in the study of cognitive aging and related mental and physical conditions. The book examines the sources of vulnerability and their consequences for Mexican-origin and for “aging in place”. By providing a combination of new knowledge, empirical evidence, and fresh approaches of dementia support in later life, this book will contribute to moving the field of Mexican-origin aging and health forward. By focusing on the serious challenges in old-age support for older people with dementia and neurocognitive disorders in two different contexts, this book will deepen academics, researchers, students and young investigators understanding of what is necessary to achieve optional care.
Understanding the Enrichment of Heavy Elements by the Chemodynamical Evolution Models of Dwarf Galaxies (Springer Theses)
by Yutaka HiraiThis book addresses the mechanism of enrichment of heavy elements in galaxies, a long standing problem in astronomy. It mainly focuses on explaining the origin of heavy elements by performing state-of-the-art, high-resolution hydrodynamic simulations of dwarf galaxies. In this book, the author successfully develops a model of galactic chemodynamical evolution by means of which the neutron star mergers can be used to explain the observed abundance pattern of the heavy elements synthesized by the rapid neutron capture process, such as europium, gold, and uranium in the Local Group dwarf galaxies. The book argues that heavy elements are significant indicators of the evolutionary history of the early galaxies, and presents theoretical findings that open new avenues to understanding the formation and evolution of galaxies based on the abundance of heavy elements in metal-poor stars.
Understanding the Generality of Mathematical Statements: An Experimental Study at the Transition from School to University (Bielefelder Schriften zur Didaktik der Mathematik #15)
by Milena DamrauIn this open access book Milena Damrau investigates the understanding of generality of mathematical statements in first-year university students and its relation to other proof-related activities. Through an experimental study, she particularly analyses the effect of different types of arguments (empirical, generic, and ordinary proofs) and statements (familiar and unfamiliar, as well as true and false ones) on several proof-related activities. The results reveal students' struggles with the concept of generality, how their understanding of generality is related to proof reading and construction and how different types of arguments and statements impact students’ performance in other proof-related activities. The findings offer valuable insights for improving mathematics courses at the transition from school to university and highlight the need for more experimental studies in mathematics education.
Understanding the Infinite
by Shaughan LavineHow can the infinite, a subject so remote from our finite experience, be an everyday tool for the working mathematician? Blending history, philosophy, mathematics, and logic, Shaughan Lavine answers this question with exceptional clarity. Making use of the mathematical work of Jan Mycielski, he demonstrates that knowledge of the infinite is possible, even according to strict standards that require some intuitive basis for knowledge.
Understanding the Mathematical Way of Thinking – The Registers of Semiotic Representations
by Raymond DuvalIn this book, Raymond Duval shows how his theory of registers of semiotic representation can be used as a tool to analyze the cognitive processes through which students develop mathematical thinking. To Duval, the analysis of mathematical knowledge is in its essence the analysis of the cognitive synergy between different kinds of semiotic representation registers, because the mathematical way of thinking and working is based on transformations of semiotic representations into others. Based on this assumption, he proposes the use of semiotics to identify and develop the specific cognitive processes required to the acquisition of mathematical knowledge. In this volume he presents a method to do so, addressing the following questions:• How to situate the registers of representation regarding the other semiotic “theories” • Why use a semio-cognitive analysis of the mathematical activity to teach mathematics • How to distinguish the different types of registers • How to organize learning tasks and activities which take into account the registers of representation • How to make an analysis of the students’ production in terms of registersBuilding upon the contributions he first presented in his classic book Sémiosis et pensée humaine, in this volume Duval focuses less on theoretical issues and more on how his theory can be used both as a tool for analysis and a working method to help mathematics teachers apply semiotics to their everyday work. He also dedicates a complete chapter to show how his theory can be applied as a new strategy to teach geometry.“Understanding the Mathematical Way of Thinking – The Registers of Semiotic Representations is an essential work for mathematics educators and mathematics teachers who look for an introduction to Raymond Duval’s cognitive theory of semiotic registers of representation, making it possible for them to see and teach mathematics with fresh eyes.”Professor Tânia M. M. Campos, PHD.
Understanding the Metaverse: Applications, Challenges, and the Future (Blockchain Technologies)
by Keshav Kaushik Gunjan ChhabraThis book highlights the numerous potentials and concerns involved with using the metaverse. Furthermore, the project discusses countermeasures to protect any firm from these risks. Insights into practical solutions may assist organizations in using this new business model by raising awareness and preparing them to improve. The book helps readers get insights into technology's future, i.e., the metaverse. The application areas of the metaverse is quite vast, but it also includes security and privacy issues. Addressing the security issues is the need of the hour. Developers are designing the applications, and users are ready to use them, but on the other side, many security issues need to be focused on. Hence, along with the applications, this book helps the reader understand these hidden security and privacy issues.
Understanding the Origin of Matter: Perspectives in Quantum Chromodynamics (Lecture Notes in Physics #999)
by David Blaschke Krzysztof Redlich Chihiro Sasaki Ludwik TurkoThis book aims at providing a solid basis for the education of the next generation of researchers in hot, dense QCD (Quantum ChromoDynamics) matter. This is a rapidly growing field at the interface of the smallest, i.e. subnuclear physics, and the largest scales, namely astrophysics and cosmology. The extensive lectures presented here are based on the material used at the training school of the European COST action THOR (Theory of hot matter in relativistic heavy-ion collisions).The book is divided in three parts covering ultrarelativistic heavy-ion collisions, several aspects related to QCD, and simulations of QCD and heavy-ion collisions. The scientific tools and methods discussed provide graduate students with the necessary skills to understand the structure of matter under extreme conditions of high densities, temperatures, and strong fields in the collapse of massive stars or a few microseconds after the big bang. In addition to the theory, the set of lectures presents hands-on material that includes an introduction to simulation programs for heavy-ion collisions, equations of state, and transport properties.
Understanding the Physics of Particle Accelerators: A Guide to Beam Dynamics Simulations Using ZGOUBI (Particle Acceleration and Detection)
by François MéotThis open access book introduces readers to the physics of particle accelerators, by means of beam dynamics simulations and exercises using the computer code ZGOUBI. The respective chapters are organized chronologically and trace the historical development of accelerators from electrostatic columns to storage rings, to the numerous variations on resonant acceleration and focusing techniques, while also addressing side aspects such as synchrotron radiation and spin dynamics. The book offers computer simulations in which readers can manipulate, guide, and accelerate charged particles and particle beams in most types of particle accelerator. By performing these simulation exercises, they will acquire a deeper understanding of charged particle beam optics, accelerator physics and technology, as well as the why and how of when to use one technology or the other. These exercises guide readers through a virtual world of accelerator and beam simulations, and involve e.g. manipulating beams for cancer therapy, producing synchrotron radiation for condensed matter research, accelerating polarized ion beams for nuclear physics research, etc. In addition to acquiring an enhanced grasp of physics, readers will discover the basic theoretical and practical aspects of particle accelerators’ main components: guiding and focusing magnets, radio-wave accelerating cavities, wigglers, etc.