Daniel Barch

Dan Barch, PhD, is a part-time faculty member of the Psychology Department and a data scientist at RTI International. He is a cognitive psychologist whose research interests include decision-making under conditions of risk and uncertainty, probabilistic reasoning, and human memory. At Tufts, Dr. Barch has taught Statistics for the Behavioral Sciences, Advanced Statistics, Experimental Design, and Reasoning and Decision Making. Dr. Barch has also worked extensively in the field of public health, producing academic papers and presentations and contributing to reports for the Department of Health and Human Services. He is the author of the upcoming book "Statistics for Everybody", due in stores and online in Fall 2019 from Kendall Hunt publishing.

Cognitive Psychology

• Nickerson, R.S., Barch, D.H., & Butler, S.F. (2018). Evaluating conditional arguments with uncertain premises. Thinking and Reasoning. Epub ahead of print.
• Daras, L. C., Ingber, M. J., Carichner, J., Barch, D., Deutsch, A., Smith, L. M., et al. (2017). Evaluating hospital readmission rates after discharge from inpatient rehabilitation. Archives of Physical Medicine and Rehabilitation 99, 1049-59.
• Nickerson, R. S., Butler, S. F., & Barch Jr., D. H. (2017). Set size, assertion form, thematic content and sampling in the selection task. Thinking and Reasoning, 23(2), 134–157.
• Barch, D. H., & Chechile, R. A. (2016). Assessing risky weighting functions for positive and negative binary gambles using the logarithmic derivative function. Journal of Mathematical Psychology, 75, 194–204.
• Chechile, R. A., & Barch, D. H. (2013). Using logarithmic derivative functions for assessing the risky weighting function for binary gambles. Journal of Mathematical Psychology, 57, 15–28.