Introducing Quantitative Methods

This exciting new core textbook offers a clear and practical introduction to quantitative methods, taking a project-based approach. The author's extensive knowledge and straightforward writing style ensure that students are steered through the process step-by-step, from developing research questions and preparing data for analysis, to explaining how to present data in appropriate formats, avoid bias, and write up results and reports. Featuring a comprehensive pedagogical framework and companion website, readers are encouraged to follow practice analyses as they go, with examples given in both SPSS and Excel, and templates are provided for students' own research. In addition to covering the research project, chapters also cover the essential mathematical and statistical analyses that are a logical consequence of posing a quantitative research methods question. This is the perfect text for all social science students studying introductory modules on quantitative methods, research methods or statistics at undergraduate or postgraduate level. It also functions as an effective guide for undergraduate and postgraduate students faced with an independent research project.

Introduction to Quantitative Research Methods is a student-friendly introduction to quantitative research methods and basic statistics. It uses a detective theme throughout the text to show how quantitative methods have been used to solve real-life problems. The book focuses on principles and techniques that are appropriate to introductory level courses in media, psychology and sociology. Examples and illustrations are drawn from historical and contemporary research in the social sciences. The original CD-ROM accompanying the book and its content are no longer available.

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. Progressing from beginner to more advanced material at an easy-to-follow pace, the author utilizes motivating examples throughout to aid readers interested in decision making and also provides critical remarks, intuitive traps, and counterexamples when appropriate. The book begins with a discussion of motivations and foundations related to the topic, with introductory presentations of concepts from calculus to linear algebra. Next, the core ideas of quantitative methods are presented in chapters that explore introductory topics in probability, descriptive and inferential statistics, linear regression, and a discussion of time series that includes both classical topics and more challenging models. The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics. Finally, the book concludes with a focus on selected tools from multivariate statistics, including advanced regression models and data reduction methods such as principal component analysis, factor analysis, and cluster analysis. The book promotes the importance of an analytical approach, particularly when dealing with a complex system where multiple individuals are involved and have conflicting incentives. A related website features Microsoft Excel® workbooks and MATLAB® scripts to illustrate concepts as well as additional exercises with solutions. Quantitative Methods is an excellent book for courses on the topic at the graduate level. The book also serves as an authoritative reference and self-study guide for financial and business professionals, as well as readers looking to reinforce their analytical skills.

This 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.

Many statements made by historians are quantitative statements, involving the use of measurable historical evidence. The historian who uses quantitative methods to analyse and interpret such information needs to be well acquainted with the particular methods and techniques of analysis and to be able to make the best use of the data that are available. There is an increasing need for training in such methods and in the interpretation of the large volume of literature now using quantitative techniques. Dr Floud’s text, which is relevant to all branches of historical inquiry, provides a straightforward and intelligible introduction for all students and research workers. The simpler and more useful techniques of descriptive and analytical statistics are described, up to the level of simple linear regression. Historical examples are used throughout, and great attention is paid to the need to ensure that the techniques are consistent with the quality of the data and with the historical problems they are intended to solve. Attention is paid to problems of the analysis of time series, which are of particular use to historians. No previous knowledge of statistics is assumed, and the simple mathematical techniques that are used are fully and clearly explained, without the use of more mathematical knowledge than is provided by an O-level course. A bibliography is provided to guide historians towards the most useful further reading. This student friendly text was first published in 1973.

This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book′s website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.

This timely and lucid guide is intended for students and scholars working on all historical periods and topics in the humanities and social sciences--especially for those who do not think of themselves as experts in quantification, "big data," or "digital humanities." The authors reveal quantification to be a powerful and versatile tool, applicable to a myriad of materials from the past. Their book, accessible to complete beginners, offers detailed advice and practical tips on how to build a dataset from historical sources and how to categorize it according to specific research questions. Drawing on examples from works in social, political, economic, and cultural history, the book guides readers through a wide range of methods, including sampling, cross-tabulations, statistical tests, regression, factor analysis, network analysis, sequence analysis, event history analysis, geographical information systems, text analysis, and visualization. The requirements, advantages, and pitfalls of these techniques are presented in layperson's terms, avoiding mathematical terminology. Conceived primarily for historians, the book will prove invaluable to other humanists, as well as to social scientists looking for a nontechnical introduction to quantitative methods. Covering the most recent techniques, in addition to others not often enough discussed, the book will also have much to offer to the most seasoned practitioners of quantification.

Presents a comprehensive introduction to analysing quantitative linguistic data. Starting with an definition of quantitative data, and how it differs from qualitative data, Seb Rasinger examines what the student linguist is trying to find out through analysing data, and how quantitative techniques can help arrive at meaningful and accurate conclusions. This expanded, 2nd edition now also includes a discussion of Analysis of Variance (ANOVA) and MANOVA, and provides a brief introduction to statistical meta-analysis. A companion website allows readers to download crib sheets and Excel templates for the main statistical tools. The book introduces: -using statistics -variables -reliability of data -describing data -analysing data -testing hypotheses -dealing with problematic data. Each chapter includes graphs and figures explaining theory through worked examples, chapter summaries, and exercises to aid student understanding. An appendix containing a summary of statistical formulae, excel commands and statistical tables is included and is an invaluable resource. Presenting a down-to-earth and readable introduction to quantitative research, this book is a useful how-to guide for students encountering quantitative data for the first time, or for postgraduates embarking on linguistic research projects.

Lecturers/instructors - request a free digital inspection copy here In the Second Edition of this textbook designed for new researchers, Uwe Flick takes readers through the process of producing a research project. The book gives readers the fundamental data collection and analysis skills that they need for their first project, as well as a good understanding of the research process as a whole. It covers both quantitative and qualitative methods, and contains plenty of real-life examples from the author's own research. The book will help readers to answer questions such as: why do social research in the first place? how do I develop a researchable question? what is a literature review and how do I conduct one? how could I collect and analyze data? what if I want to do my research online? Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--