Understanding and Applying Research Design

A fresh approach to bridging research design with statistical analysis

While good social science requires both research design and statistical analysis, most books treat these two areas separately. Understanding and Applying Research Design introduces an accessible approach to integrating design and statistics, focusing on the processes of posing, testing, and interpreting research questions in the social sciences.

The authors analyze real-world data using SPSS software, guiding readers on the overall process of science, focusing on premises, procedures, and designs of social scientific research. Three clearly organized sections move seamlessly from theoretical topics to statistical techniques at the heart of research procedures, and finally, to practical application of research design:

• Premises of Research introduces the research process and the capabilities of SPSS, with coverage of ethics, Empirical Generalization, and Chi Square and Contingency Table Analysis
• Procedures of Research explores key quantitative methods in research design including measurement, correlation, regression, and causation
• Designs of Research outlines various design frameworks, with discussion of survey research, aggregate research, and experiments

Throughout the book, SPSS software is used to showcase the discussed techniques, and detailed appendices provide guidance on key statistical procedures and tips for data management. Numerous exercises allow readers to test their comprehension of the presented material, and a related website features additional data sets and SPSS code.

Understanding and Applying Research Design is an excellent book for social sciences and education courses on research methods at the upper-undergraduate level. The book is also an insightful reference for professionals who would like to learn how to pose, test, and interpret research questions with confidence.

Nyckelord: Statistics for Social Sciences, social sciences, research, applied research, research design, statistics, measurement, causation, causal models, correlation, regression analysis, SPSS software