Interdisciplinary profile area FAIR starts work
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The IFS was instrumental in attracting the interdisciplinary profile area From Prediction to Agile Interventions in the Social Sciences (FAIR), which is funded by the North Rhine-Westphalian Ministry of Culture and Science for the next three years. Professor Fani Lauermann is leading the project together with statistics professor Philipp Doebler. FAIR brings together researchers from data sciences, statistics, education sciences, psychology, rehabilitation studies, and sociology to develop innovative methods of data analysis to address societal challenges in highly relevant areas such as education, health, and participation. Building this bridge is important because increasingly larger and more complex data, such as from longitudinal studies in empirical education research and life course data from sociological aging research, can contribute to sophisticated predictions and a deep understanding of interrelationships. In the social sciences, increasingly larger and more complex data are available that can contribute to more accurate predictive models (e.g., for outcomes such as school success, health, and well-being) and improve our understanding of cause-effect relationships.