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Quantile Regression
by Lingxin Hao Daniel Q. NaimanQuantile Regression, the first book of Hao and Naiman's two-book series, establishes the seldom recognized link between inequality studies and quantile regression models. Though separate methodological literature exists for each subject, the authors seek to explore the natural connections between this increasingly sought-after tool and research topics in the social sciences. Quantile regression as a method does not rely on assumptions as restrictive as those for the classical linear regression; though more traditional models such as least squares linear regression are more widely utilized, Hao and Naiman show, in their application of quantile regression to empirical research, how this model yields a more complete understanding of inequality. Inequality is a perennial concern in the social sciences, and recently there has been much research in health inequality as well. Major software packages have also gradually implemented quantile regression. Quantile Regression will be of interest not only to the traditional social science market but other markets such as the health and public health related disciplines.Key Features:Establishes a natural link between quantile regression and inequality studies in the social sciences Contains clearly defined terms, simplified empirical equations, illustrative graphs, empirical tables and graphs from examples Includes computational codes using statistical software popular among social scientists Oriented to empirical research
Quantitative Analysis and IBM® SPSS® Statistics
by Abdulkader AljandaliThis guide for practicing statisticians and data scientists who use IBM SPSS for statistical analysis of big data in business and finance is the first of a two-part guide to SPSS for Windows, introducing data entry into SPSS, along with elementary statistical and graphical methods for summarizing and presenting data. Part I also covers the rudiments of hypothesis testing and business forecasting while Part II will present multivariate statistical methods, more advanced forecasting methods, and multivariate methods. IBM SPSS offers a powerful set of statistical and information analysis systems that run on a wide variety of personal computers. The Windows version of SPSS is built around routines that have been developed, tested, and widely used for more than 20 years. As such, SPSS is extensively used in industry, commerce, banking, local and national governments, and education. Just a small subset of users of the package include the major clearing banks, the BBC, British Gas, British Airways, British Telecom, the Consumer Association, Eurotunnel, Glaxo, ICI, London Underground, the NHS, Plessey, Shell, Unilever, and W. H. Smith and Son. Although the emphasis in this guide is on applications of SPSS for Windows, there is a need for users to be aware of the statistical assumptions and rationales underpinning correct and meaningful application of the techniques available in the packa≥ therefore, such assumptions are discussed, and methods of assessing their validity are described. Also presented is the logic underlying the computation of the more commonly used test statistics in the area of hypothesis testing. Mathematical background is kept to a minimum.
Quantitative Analysis in Archaeology
by Todd L. VanPool Robert D. LeonardQuantitative Analysis in Archaeology introduces the application of quantitative methods in archaeology. It outlines conceptual and statistical principles, illustrates their application, and provides problem sets for practice. Discusses both methodological frameworks and quantitative methods of archaeological analysis Presents statistical material in a clear and straightforward manner ideal for students and professionals in the field Includes illustrative problem sets and practice exercises in each chapter that reinforce practical application of quantitative analysis
A Quantitative Analysis of Regional Well-Being: Identity and Gender in India, South Africa, the USA and the UK (Routledge Studies in Development Economics)
by Vani Kant BorooahUsing data from the World Values Survey, this book sheds light on the link between happiness and the social group to which one belongs. The work is based on a rigorous statistical analysis of differences in the probability of happiness and life satisfaction between the predominant social group and subordinate groups. The cases of India and South Africa receive deep attention in dedicated chapters on cast and race, with other chapters considering issues such as cultural bias, religion, patriarchy, and gender. An additional chapter offers a global perspective. On top of this, the longitudinal nature of the data facilitates an examination of how world happiness has evolved between 1994 and 2014. This book will be a valuable reference for advanced students, scholars and policymakers involved in development economics, well-being, development geography, and sociology.
Quantitative and Statistical Research Methods
by William E. Martin Krista D. BridgmonQuantitative and Statistical Research Methods This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles. Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to: Pinpoint research questions and hypotheses Identify, classify, and operationally define the study variables Choose appropriate research designs Conduct power analysis Select an appropriate statistic for the problem Use a data set Conduct data screening and analyses using SPSS Interpret the statistics Write the results related to the problem Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.
Quantitative Datenanalyse: Eine Einführung mit SPSS (Studientexte zur Soziologie)
by Markus TausendpfundDas Buch bietet eine Einführung in die quantitative Datenanalyse mit dem Statistikprogramm SPSS. Es werden Kenntnisse vermittelt, um einfache Analysen selbstständig durchführen zu können. Dazu gehören der Download von Sekundärdatensätzen, die sachgemäße Kodierung von Variablen (Datenaufbereitung), die uni- und bivariate Datenanalyse sowie multivariate Analyseverfahren. Für eine möglichst praxisnahe Darstellung werden die einzelnen Analysen auf Basis der ALLBUS-Daten 2014 illustriert. Dabei werden die zentralen Befehle (Syntax) vorgestellt, die für die Datenanalyse mit SPSS erforderlich sind.
Quantitative Datenanalyse: Eine Einführung mit SPSS (Studientexte zur Soziologie)
by Markus TausendpfundDas Buch bietet eine Einführung in die quantitative Datenanalyse mit dem Statistikprogramm SPSS. Es werden Kenntnisse vermittelt, um einfache Analysen selbstständig durchführen zu können. Dazu gehören der Download von Sekundärdatensätzen, die sachgemäße Kodierung von Variablen (Datenaufbereitung), die uni- und bivariate Datenanalyse sowie multivariate Analyseverfahren. Für eine möglichst praxisnahe Darstellung werden die einzelnen Analysen auf Basis der ALLBUS-Daten 2018 illustriert. Dabei werden die zentralen Befehle (Syntax) vorgestellt, die für die Datenanalyse mit SPSS erforderlich sind.
Quantitative Demography and Health Estimates: Healthy Life Expectancy, Templates for Direct Estimates from Life Tables and other Applications (The Springer Series on Demographic Methods and Population Analysis #55)
by Christos H Skiadas Charilaos SkiadasThis book provides new theoretic and applied material with focus on quantitative methods and data analysis techniques applied in demography, population studies, health issues and statistics. It discusses the quantitative techniques to estimate the healthy life expectancy by expanding the classical life tables to include the proportion with disability calculated from life tables, along with the Sullivan method. The provided templates apply immediately to the life tables from WHO, HMD, Eurostat and other life table providers. Furthermore, the book explores the possibility of creating new health indicators along with Covid-19 pandemic management, factors associated to loneliness and an alcohol indicator. Part of the book is devoted to mortality, epidemic models, and the supercentenarians age estimation. Data analysis and artificial intelligence methods are included to apply in demographic and socio-economic cases. By providing a methodology to cope with health problems in demography and society by quantifying important health parameters, this book is a valuable guide for researchers, theoreticians, and practitioners from various disciplines and especially health scientists, statisticians, economists, and sociologists.
Quantitative Methodologies using Multi-Methods: Models for Social Science and Information Technology Research
by Kweku-Muata Osei-Bryson Sergey SamoilenkoQuantitative Methodologies using Multi-Methods is a multifaceted book written to help researchers. It is a user-friendly introduction to the popular methods of data mining and data analysis. The book avoids getting involved into details that are more suitable for more advanced users; it is written for readers who have, at most, a surface-level knowledge of the methods presented in the book. The book also serves as an introductory guide to the subject of complementarity of the tools and techniques of data analysis. It shows how methods could be used in synergy to offer insights into the issues that could not be dissected by any single method alone. This text can also be used as a set of templates, where, given a set of research questions, the investigator could identify a set of methodological modules allowing for answering the research questions of interest. This is not entirely unlike the relationship between analysis and design phases of the systems development life cycle — where the "What?" of the analysis phase has to be translated into the "How" of the design phase. The book can guide the identification of modules (the "How") that are suitable for answering research questions (the "What"). It can aid in transitioning a conceptual domain of the research questions into a scaffolding of data analytic and data mining methods. The book is also a guide to exploring what data under investigation holds. For example, an investigator may use the methodological modules presented in this book to generate a set of preliminary questions which, after a careful consideration and a requisite culling, could be formulated into a set of questions consistent within a selected theory or a framework. Finally, the book can be used as a generator of new research questions. Applying every method in each of the book’s modules opens a new dimension ripe with follow-up questions such as, "Why is this so?" The answers to this question may provide new insight and lead to the development of a new theory.
Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in SPSS and Stata
by Daniel StockemerThis textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
Quantitative Methods for the Social Sciences: A Practical Introduction with Examples in R (Springer Texts in Political Science and International Relations)
by Daniel Stockemer Jean-Nicolas BordeleauThis textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R. Building on the premise that we need to teach statistical methods in a holistic and practical format, the book guides students through the four main elements of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. In detail, students will learn how to create their own questionnaire on the basis of formulating hypotheses; sampling participants; disseminating their questionnaire; creating datasets; and analyzing their data. The data analytical sections of this revised and extended edition explain the theory, rationale and mathematical foundations of relevant bivariate and multi-variate statistical tests. These include the T-test, F-test, Chi-square test and correlation analyses, as well as bivariate and multivariate regression analyses. In addition, the book offers a brief introduction to statistical computing with R, which includes clear instructions on how to conduct these statistical tests in R. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research and quantitative methods classes in the social sciences.
Quantitative Methods in Demography: Methods and Related Applications in the Covid-19 Era (The Springer Series on Demographic Methods and Population Analysis #52)
by Christos H. Skiadas Charilaos SkiadasThis book provides quantitative and applied methodologies in the Covid-19 era exploring important issues in demography, population studies, and health. It provides insight into health and health measures as to the healthy life years lost and the healthy life expectancy related to Covid-19 pandemic. It also describes mortality and survival and focuses on data analysis in demography and population studies. Special methods and applications in demography and society are also described, thereby including applications in society, pension and insurance. As such, this book is a valuable guide for researchers, theoreticians and practitioners from various scientific fields.
Quantitative Methods in Tourism Economics
by Manuela Sarmento Álvaro Matias Peter NijkampTourism economics is partly based on established principles from the economics discipline, but it also incorporates elements from sociology, psychology, organization theory and ecology. It has over the years turned into an appealing multi-disciplinary oriented approach to the understanding of the impacts of leisure time in a modern society, including cultural heritage, sustainable quality of life, and industrial organization of the hospitality industry. The increasing dynamics in the tourist industry and its worldwide effects will continue to attract the attention of both the research and the policy sector in the years to come. Rather than speculating on non-observed facts, there is a clear need for evidence-based research in order to map out the complex dynamics of the tourist industry. The present volume comprises novel studies - mainly of a quantitative-analytical nature - on the supply, demand and contextual aspects of modern tourism. It contains a sound mix of theory, methodology, policy and case studies on various tourism issues in different parts of the world.
Quantitative Research Methods in Communication: The Power of Numbers for Social Justice (Routledge Social Justice Communication Activism Series)
by Erica Scharrer Srividya RamasubramanianThis textbook is an advanced introduction to quantitative methods for students in communication and allied social science disciplines that focuses on why and how to conduct research that contributes to social justice. Today’s researchers are inspired by the potential for scholarship to make a difference for society, to push toward more just and equitable ends, and to engage in dialogue with members of the public so that they can make decisions about how to navigate the social, cultural, and political world equipped with accurate, fair, and up-to-date knowledge. This book illustrates the mechanics and the meaning behind quantitative research methods by illustrating each step in the research design process with research addressing questions of social justice. It provides practical guidance for researchers who wish to engage in the transformation of structures, practices, and understandings in society through community and civic engagement and policy formation. It contains step-by-step guidance in quantitative methods—from conceptualization through all the stages of execution of a study, including providing a detailed guide for statistical analysis—and demonstrates how researchers can engage with social justice issues in systematic, rigorous, ethical, and meaningful ways. This text serves as a core or supplementary textbook for graduate and advanced undergraduate courses in research methods for communication and social sciences and fills a gap for a methods text that is responsive to the desire of scholars to conduct socially impactful research.
Quantitative Research Methods in Communication: The Power of Numbers for Social Justice (Routledge Social Justice Communication Activism Series)
by Erica Scharrer Srividya RamasubramanianThis fully updated second edition offers an advanced introduction to quantitative methods that focuses on why and how to conduct research that contributes to social justice.Providing both inspiration and step-by-step guidance on how to conceive, design, and carry out a quantitative study, the book shows how research can be used to work toward a more just and equitable world. The authors provide a detailed guide to quantitative methods and statistical analysis, showing how researchers can engage with social justice issues in systematic, rigorous, ethical, and meaningful ways. This new edition includes a new chapter on writing literature reviews and better aligns with the stages of quantitative research as well as the changing technologies that are available for researchers to both study and use in their work. It includes updated real-world case studies, interviews with scholar-activists, and definitions of key concepts as well as a deeper focus on ethics, social media, computational social sciences, data analytics, and data visualization techniques.Attuned to questions of access, equity, justice, diversity, and inclusion, this textbook is ideal for graduate and advanced undergraduate courses in research methods for communication and the social sciences. It will also be of interest to researchers who wish to engage with the transformation of structures, practices, and understandings in society through community and civic engagement and policy formation.Online resources for instructors include a test bank, PowerPoint slides, sample dataset, and YouTube tutorials. They are available online at www.routledge.com/9781032599878.
Quantitative Research on Street Interface Morphology: Comparison Between Chinese and Western Cities
by Yu ZhouThis book investigates the historical evolution, regional differences, and quantitative measurement on street interface, which forms the street space and plays a very important role in urban form. Empirical research reveals the street interface in Chinese cities are much more complicated than European and American cities. This book explores the reason and reveals the relationship between street interface and urban form in morphology. By constructing quantitative measurement method on street interface morphology, quantitative parameters can be used in urban planning guidelines in China. Both researchers and students working in architecture, urban design, urban planning and urban studies can benefit from this book.
Quantitative Social Research Methods
by Kultar SinghQuantitative Social Research Methods explores the entire spectrum of quantitative social research methods and their application, with special reference to the development sector. It provides detailed coverage of all statistical research and analysis method with an emphasis on multivariate analysis techniques, such as regression discriminant analysis, logistic regression, factor, factor, cluster, correspondence and conjoint analysis. The book is thematically arranged in two sections: the first section introduces development research techniques, explores the genesis and scope of social research, research processes and then goes on to explain univariate, bivariate and multivariate data analysis with the help of software packages such as SPSS and STATA. The second focuses on the application of social and development research methods in the development sector. It explores research method application and the issues relevant to aspects of development such as population, health and nutrition, poverty and rural development, education, water and sanitation, and environment and natural resource management.
Quantitative Social Science: An Introduction
by Kosuke ImaiAn introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fieldsQuantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as economics, sociology, public policy, and data science.Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the R programming language and to interpret the results—it encourages hands-on learning, not paper-and-pencil statistics. More than forty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior.Proven in the classroom, this one-of-a-kind textbook features numerous additional data analysis exercises and interactive R programming exercises, and also comes with supplementary teaching materials for instructors.Written especially for students in the social sciences and allied fields, including economics, sociology, public policy, and data scienceProvides hands-on instruction using R programming, not paper-and-pencil statisticsIncludes more than forty data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slidesLooking for a more accessible introduction? Consider Data Analysis for Social Science by Elena Llaudet and Kosuke Imai, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.
Quantitative Social Science: An Introduction in Stata
by Kosuke Imai Lori D. BougherThe Stata edition of the groundbreaking textbook on data analysis and statistics for the social sciences and allied fieldsQuantitative analysis is an increasingly essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it—or if they do, they usually end up in statistics classes that offer few insights into their field. This textbook is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, such as business, economics, education, political science, psychology, sociology, public policy, and data science.Quantitative Social Science engages directly with empirical analysis, showing students how to analyze data using the Stata statistical software and interpret the results—it emphasizes hands-on learning, not paper-and-pencil statistics. More than fifty data sets taken directly from leading quantitative social science research illustrate how data analysis can be used to answer important questions about society and human behavior.Proven in classrooms around the world, this one-of-a-kind textbook features numerous additional data analysis exercises, and also comes with supplementary teaching materials for instructors.Written especially for students in the social sciences and allied fields, including business, economics, education, psychology, political science, sociology, public policy, and data scienceProvides hands-on instruction using Stata, not paper-and-pencil statisticsIncludes more than fifty data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and interactive programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
Quantitative Social Science: An Introduction in Tidyverse
by Kosuke Imai Nora Webb WilliamsA tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields <p><p>Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior. <p><p>Emphasizes hands-on learning, not paper-and-pencil statistics <p><p>Includes data sets from actual research for students to test their skills on <p><p>Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools <p><p>Features a wealth of supplementary exercises, including additional data analysis exercises and programming exercises <p><p>Offers a solid foundation for further study <p><p>Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
Quantitative Social Science: An Introduction in tidyverse
by Kosuke Imai Nora Webb WilliamsA tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fieldsQuantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior.Emphasizes hands-on learning, not paper-and-pencil statisticsIncludes data sets from actual research for students to test their skills onCovers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical toolsFeatures a wealth of supplementary exercises, including additional data analysis exercises and programming exercisesOffers a solid foundation for further studyComes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides
Quantitative Social Science Data with R: An Introduction
by Brian J Fogarty"A great, action-oriented book for novice data analysts. If you have no background in quantitative social science, Fogarty's book gives you a toolbox for starting statistical analysis and developing your skills" - Jamie Monogan, Associate Professor of Political Science, University of Georgia Relevant, engaging, and packed with student-focused learning features, this book provides the step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and R, it uses examples from across the social sciences to show you how to apply abstract statistical and methodological principles to your own work. At a student-friendly pace, it enables you to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives you not only the tools you need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what you have learned. Brian J. Fogarty is a Lecturer in Quantitative Social Science on the Glasgow Q-Step Programme in the School of Social and Political Sciences at the University of Glasgow.
Quantitative Social Science Data with R: An Introduction
by Brian J Fogarty"A great, action-oriented book for novice data analysts. If you have no background in quantitative social science, Fogarty's book gives you a toolbox for starting statistical analysis and developing your skills" - Jamie Monogan, Associate Professor of Political Science, University of Georgia Relevant, engaging, and packed with student-focused learning features, this book provides the step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and R, it uses examples from across the social sciences to show you how to apply abstract statistical and methodological principles to your own work. At a student-friendly pace, it enables you to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives you not only the tools you need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what you have learned. Brian J. Fogarty is a Lecturer in Quantitative Social Science on the Glasgow Q-Step Programme in the School of Social and Political Sciences at the University of Glasgow.
Quantitative Social Science Data with R: An Introduction
by Brian J FogartyRelevant, engaging, and packed with student-focused learning features, this book provides the basic step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and the language and functionality of R and R Studio software, it uses examples from across the social sciences to show students how to apply abstract statistical and methodological principles to their own work. Maintaining a student-friendly pace, it goes beyond a normal introductory statistics book and shows students where data originates and how to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives students not only the tools they need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what they have learned.
Quantitative Social Science Data with R: An Introduction
by Brian J FogartyRelevant, engaging, and packed with student-focused learning features, this book provides the basic step-by-step introduction to quantitative research and data every student needs. Gradually introducing applied statistics and the language and functionality of R and R Studio software, it uses examples from across the social sciences to show students how to apply abstract statistical and methodological principles to their own work. Maintaining a student-friendly pace, it goes beyond a normal introductory statistics book and shows students where data originates and how to: - Understand and use quantitative data to answer questions - Approach surrounding ethical issues - Collect quantitative data - Manage, write about, and share the data effectively Supported by incredible digital resources with online tutorials, videos, datasets, and multiple choice questions, this book gives students not only the tools they need to understand statistics, quantitative data, and R software, but also the chance to practice and apply what they have learned.