Surveying Cultures. Discovering Shared Conceptions and Sentiments
Автор: David Heise R.
Год издания:
Surveying Cultures uniquely employs techniques rooted in survey methodology to discover cultural patterns in social science research. Examining both classical and emerging methods that are used to survey and assess differing norms among populations, the book successfully breaks new ground in the field, introducing a theory of measurement for ethnographic studies that employs the consensus-as-culture model. The book begins with a basic overview of cross-cultural measurement of sentiments and presents innovative and sophisticated analyses of measurement issues and of homogeneity among respondents. Subsequent chapters explore topics that are at the core of successful data collection and analysis in culture studies, including: The role of bipolar scales and Internet data collection in measuring sentiments Key methodological variables that determine the quality of quantitative data, including measurement errors, validity, and reliability New approaches to reliability and several new methods of assessing a respondent's degree of inculcation into group culture Sampling, coverage, nonresponse, and measurement errors, with an in-depth discussion of their occurrence in culture surveys, their impact assessments, and how current measurement techniques are constructed to help prevent these kinds of errors Common problems often encountered in the acquisition and communication of data, including identifying error variances, interpreting gender differences in responses, and defining the difference between cultures and subcultures Throughout the book, each topic is accompanied by a review of related methodological literature. For many of the presented concepts, the author includes a formal analysis of the related issues in measuring cultural norms and reports on analyses. Each chapter concludes with an organized list of major findings as well as an insightful outline of specific recommendations regarding practical problems in culture studies. Surveying Cultures serves as a valuable supplemental book to courses on survey and research methods at the upper-undergraduate and graduate levels. It is also an excellent reference for researchers in the fields of sociology, anthropology, psychology, and political science.
Model-Based Testing Essentials - Guide to the ISTQB Certified Model-Based Tester
Автор: Bruno Legeard
Год издания:
Provides a practical and comprehensive introduction to the key aspects of model-based testing as taught in the ISTQB® Model-Based Tester—Foundation Level Certification Syllabus This book covers the essentials of Model-Based Testing (MBT) needed to pass the ISTQB® Foundation Level Model-Based Tester Certification. The text begins with an introduction to MBT, covering both the benefits and the limitations of MBT. The authors review the various approaches to model-based testing, explaining the fundamental processes in MBT, the different modeling languages used, common good modeling practices, and the typical mistakes and pitfalls. The book explains the specifics of MBT test implementation, the dependencies on modeling and test generation activities, and the steps required to automate the generated test cases. The text discusses the introduction of MBT in a company, presenting metrics to measure success and good practices to apply. Provides case studies illustrating different approaches to Model-Based Testing Includes in-text exercises to encourage readers to practice modeling and test generation activities Contains appendices with solutions to the in-text exercises, a short quiz to test readers, along with additional information Model-Based Testing Essentials – Guide to the ISTQB® Certified Model-Based Tester – Foundation Level is written primarily for participants of the ISTQB® Certification: software engineers, test engineers, software developers, and anybody else involved in software quality assurance. This book can also be used for anyone who wants a deeper understanding of software testing and of the use of models for test generation.