For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.

This book offers postgraduate and early career researchers in accounting and information systems a guide to choosing, executing and reporting appropriate data analysis methods to answer their research questions. It provides readers with a basic understanding of the steps that each method involves, and of the facets of the analysis that require special attention. Rather than presenting an exhaustive overview of the methods or explaining them in detail, the book serves as a starting point for developing data analysis skills: it provides hands-on guidelines for conducting the most common analyses and reporting results, and includes pointers to more extensive resources. Comprehensive yet succinct, the book is brief and written in a language that everyone can understand - from students to those employed by organizations wanting to study the context in which they work. It also serves as a refresher for researchers who have learned data analysis techniques previously but who need a reminder for the specific study they are involved in.

In Analysing Quantitative Survey Data, Jeremy Dawson introduces you to the key elements of analysing quantitative survey data using classical test theory, the measurement theory that underlies the techniques described in the book. The methodological assumptions, basic components and strengths and limitations of this analysis are explained and with the help of illustrative examples, you are guided through how to conduct the key procedures involved, including reliability analysis, exploratory and confirmatory factor analysis. Ideal for Business and Management students reading for a Master’s degree, each book in the series may also serve as reference books for doctoral students and faculty members interested in the method. Part of SAGE’s Mastering Business Research Methods series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practical guidance on using a chosen method of data collection or analysis.

This innovative book provides a fresh take on quantitative data analysis within the social sciences. It presents variable-based and case-based approaches side-by-side encouraging you to learn a range of approaches and to understand which is the most appropriate for your research. Using two multidisciplinary non-experimental datasets throughout, the book demonstrates that data analysis is really an active dialogue between ideas and evidence. Each dataset is returned to throughout the chapters enabling you to see the role of the researcher in action; it also showcases the difference between each approach and the significance of researchers’ decisions that must be made as you move through your analysis. The book is divided into four clear sections: Data and their presentation Variable-based analyses Case-based analyses Comparing and combining approaches Clear, original and written for students this book should be compulsory reading for anyone looking to conduct non-experimental quantitative data analysis.

Quantitative data analysis is now a compulsory component of most degree courses in the social sciences and students are increasingly reliant on computers for the analysis of data. Quantitative Data Analysis with Minitab explains statistical tests for Minitab users using the same formulae free, non technical approach, as the very successful SPPS version. Students will learn a wide range of quantitative data analysis techniques and become familiar with how these techniques can be implemented through the latest version of Minitab. Techniques covered include univariate analysis (with frequency table, dispersion and histograms), bivariate (with contingency tables correlation, analysis of varience and non-parametric tests) and multivariate analysis (with multiple regression, path analysis, covarience and factor analysis). In addition the book covers issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. Each chapter concludes with a set of exercises. Social science students will welcome this integrated, non mathematical introduction to quantitative data anlysis and the minitab package.

In Analysing Quantitative Data, Charles A. Scherbaum and Kristen M. Shockley guide the reader through Understanding Quantitative Data Analysis, Basic Components of Quantitative Data Analysis, Conducting Quantitative Data Analysis, Examples of Quantitative Data Analysis and Conclusions. An appendix contains Excel Formulas. Ideal for Business and Management students reading for a Master’s degree, each book in the series may also serve as reference books for doctoral students and faculty members interested in the method. Part of SAGE’s Mastering Business Research Methods Series, conceived and edited by Bill Lee, Mark N. K. Saunders and Vadake K. Narayanan and designed to support researchers by providing in-depth and practical guidance on using a chosen method of data collection or analysis.

An accessible and user-friendly guide to quantitative data analysis in educational research, aimed at those with little or no prior knowledge of statistical methods.

"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"--

Research Methods: Information, Systems, and Contexts, Second Edition, presents up-to-date guidance on how to teach research methods to graduate students and professionals working in information management, information science, librarianship, archives, and records and information systems. It provides a coherent and precise account of current research themes and structures, giving students guidance, appreciation of the scope of research paradigms, and the consequences of specific courses of action. Each of these valuable sections will help users determine the relevance of particular approaches to their own questions. The book presents academics who teach research and information professionals who carry out research with new resources and guidance on lesser-known research paradigms. - Provides up-to-date knowledge of research methods and their applications - Provides a coherent and precise account of current research themes and structures through chapters written by authors who are experts in their fields - Helps students and researchers understand the range of quantitative and qualitative approaches available for research, as well as how to make practical use of them - Provides many illustrations from projects in which authors have been involved, to enhance understanding - Emphasises the nexus between formulation of research question and choice of research methodology - Enables new researchers to understand the implications of their planning decisions