Publication Date
2015
Document Type
Thesis
Committee Members
Kevin Bennett (Committee Member), John Flach (Advisor), Joseph Houpt (Committee Member)
Degree Name
Master of Science (MS)
Abstract
Can humans discriminate whether strings of events (e.g., shooting success in basketball) were generated by a random or constrained process (e.g., hot and cold streaks)? Conventional wisdom suggests that humans are not good at this discrimination. Following from Cooper, Hammack, Lemasters, and Flach (2014), a series of Monte Carlo simulations and an empirical experiment examined the abilities of both humans and statistical tests (Wald-Wolfowitz Runs Test and 1/f) to detect specific constraints that are representative of plausible factors that might influence the performance of athletes (e.g., learning, non-stationary task constraints). Using a performance/success dependent learning constraint that was calibrated to reflect shooting percentages representative of shooting in NBA games, we found that the conventional null hypothesis tests were unable to detect this constraint as being significantly different from random. Interestingly however, the analysis of human performance showed that people were able to make this discrimination reliably better than chance. Hence, people may also be able to detect patterned/constrained processes in a real-world setting (e.g., streaks in basketball performance), thus supporting the belief in the hot hand.
Page Count
72
Department or Program
Department of Psychology
Year Degree Awarded
2015
Copyright
Copyright 2015, some rights reserved. My ETD may be copied and distributed only for non-commercial purposes and may not be modified. All use must give me credit as the original author.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
