The Philosophy of Circular Statistical Thinking in Human Cognition, Temporal Constructs & Anthropological Studies
Main Article Content
Abstract
Circular statistical thinking addresses data that exhibit periodicity or directionality, such as angles, times, or compass bearings, and finds broad applications across the social and natural sciences, especially relevant for interdisciplinary fields exploring the cyclical nature of cultural rituals, seasonal festivals, migratory patterns, and human cognition. This research aims to bridge the gap between circular statistical methods and philosophical-anthropological inquiries. The objectives are: (1) to examine philosophical underpinnings of cyclicity in human thought, (2) to apply circular statistical frameworks in anthropological analyses of recurring cultural and social behaviors, and (3) to illustrate how periodicity shapes human cognition and cultural organization. Employing an interdisciplinary methodology, we integrate philosophical reasoning with statistical modeling tailored for circular data. We carry out simulation based case studies and theoretical demonstrations to showcase how circular statistics (e.g., von Mises distribution, phase synchronization) can elucidate periodic behaviors in cultural contexts. Our findings demonstrate that circular statistical thinking offers robust quantitative tools for analyzing cyclical human activities, from seasonal and ritual practices to social synchronization. By highlighting mean directions, dispersion, and synchronization metrics, we reveal how periodic structures inform social cohesion and collective identities. This approach contributes new perspectives on the interplay between statistical modeling, human cognition, and cultural evolution, extending the applicability of circular statistics to broader inquiries into human nature and culture.
Downloads
Article Details

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abashin, S. N. (2019). Returning home and circular mobility: How crises change the anthropological view of migration. Anthropology & Archeology of Eurasia, 58(3), 155–168. https://doi.org/10.1080/10611959.2019.1686902
Bandyopadhyay, P. S., & Forster, M. R. (2011). Philosophy of statistics: An introduction. Philosophy of statistics, 7, 1–50. DOI: 10.1016/B978-0-444-51862-0.50001-0
Cremers, J., & Klugkist, I. (2018). One direction? a tutorial for circular data analysis using r with examples in cognitive psychology. Frontiers in psychology, 9, 2040. https://doi.org/10.3389/fpsyg.2018.02040
Gell, A. (2021). The anthropology of time: Cultural constructions of temporal maps and images. Routledge. https://doi.org/10.4324/9781003135180
Gelman, A., & Shalizi, C. R. (2013). Philosophy and the practice of bayesian statistics. British Journal of Mathematical and Statistical Psychology, 66(1), 8-38. https://doi.org/10.1111/j.2044-8317.2011.02037.x
Good, I. (1988). The interface between statistics and philosophy of science. Statistical Science, 3(4), 386–397. DOI: 10.1214/ss/1177012754
Haun, D. B., Jordan, F. M., Vallortigara, G., & Clayton, N. S. (2010). Origins of spatial, temporal and numerical cognition: Insights from comparative psychology. Trends in Cognitive Sciences, 14(12), 552–560. https://doi.org/10.1016/j.tics.2010.09.006
Jammalamadaka, S. R., & SenGupta, A. (2001). Topics in Circular Statistics. World Scientific.
Kowalski C. J. (1972). A commentary on the use of multivariate statistical methods in anthropometric research. American journal of physical anthropology, 36(1), 119–132. https://doi.org/10.1002/ajpa.1330360114
Kriegeskorte, N., Lindquist, M. A., Nichols, T. E., Poldrack, R. A., & Vul, E. (2010). Everything you never wanted to know about circular analysis, but were afraid to ask. Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 30(9), 1551–1557. https://doi.org/10.1038/jcbfm.2010.86
Lindley, D. V. (2000). The philosophy of statistics. Journal of the Royal Statistical Society. Series D (The Statistician), 49(3), 293-337.
Robbins, J. (2007). Continuity thinking and the problem of christian culture: belief, time, and the anthropology of christianity. Current anthropology, 48(1), 5-38. https://doi.org/10.1086/508690
Romeijn, J.-W. (2014). Philosophy of statistics. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy (pp. 1-86) http://plato.stanford.edu/archives/win2014/entries/statistics/
Schumm, W., Crawford, D., Barkey, P., Bush, D., & Bosch, D. (2021). Using statistics to analyze anthropological/religious issues from the distant past. Insights of Anthropology, 5(1), 337–346. DOI: 10.36959/763/520
Shweder, R. A., Casagrande, J. B., Fiske, D. W., Greenstone, J. D., Heelas, P., Laboratory of Comparative Human Cognition, and Lancy, D. F. (1977). Likeness and likelihood in everyday thought: magical thinking in judgments about personality [and comments and reply]. Current anthropology, 18(4), 637–658. https://doi.org/10.1086/201974
Sinha, C., Sinha, V. D. S., Zinken, J., & Sampaio, W. (2011). When time is not space: The social and linguistic construction of time intervals and temporal event relations in an Amazonian culture. Language and Cognition, 3(1), 137–169. DOI: 10.1515/langcog.2011.006
Starmans, R. J. C. M. (2018). The Predicament of Truth: On Statistics, Causality, Physics, and the Philosophy of Science. In M. J. van der Laan, S Rose (Eds.), Targeted Learning in Data Science (pp. 561-584). Springer, Cham. https://doi.org/10.1007/978-3-319-65304-4_30
Suppes, P. (2007). Statistical concepts in philosophy of science. Synthese, 154, 485–496. https://doi.org/10.1007/s11229-006-9122-0
Veissière, S. P. L., Constant, A., Ramstead, M. J. D., Friston, K. J., & Kirmayer, L. J. (2019). Thinking through other minds: A variational approach to cognition and culture. The Behavioral and brain sciences, 43, e90. https://doi.org/10.1017/S0140525X19001213
Wallace, A. F. (1962). Culture and cognition. Science (New York, N.Y.), 135(3501), 351–357. https://doi.org/10.1126/science.135.3501.351
Yates, F., & Healy, M. J. (1951). Statistical methods in anthropology. Nature, 168(4287), 1116–1117. https://doi.org/10.1038/1681116a0