This kind of exploratory data analysis depends on effective visualization techniques. In our case, the key design advance was the Group-in-a-Box layout technique, which presents the results of ...

Missing data present a perennial challenge in scientific research, potentially undermining the validity of conclusions if not addressed rigorously. The analysis of missing data encompasses a broad ...

SM seeks qualitative and quantitative contributions that address the full range of methodological problems confronted by empirical research in the social sciences, including conceptualization, data ...

Make the transition from psychology student to data scientist with our MSc. This course combines practical training in the latest research techniques with classes in computational data analysis.

Four integrative data analysis strategies for mixed-method evaluation designs are derived from and illustrated by empirical practice: data transformation, typology development, extreme case analysis, ...

Skills in the preparation and analysis of complex, big data sets for research in Social Sciences and Computational Social Science. Skills needed to present their research effectively, using ...

Data sources The analysis in this report is based on the combination of work requirements and job skills data from the U.S. Department of Labor’s ...

This analysis was done by Jordan Rau, a senior correspondent, and Holly K. Hacker, a data editor, both with KFF Health News, part of KFF, a nonprofit health-policy research, polling and news ...