Part 1 of the 2019 UA College of Science Lecture Series "Searching for Certainty"
Lecturer: Joanna Masel, Professor of Ecology and Evolutionary Biology, University of Arizona
Not every scientific study gets the answer right. Answers we get from “mining” existing datasets are particularly vulnerable to confounding factors. In contrast, gold-standard experiments, where subjects are randomly assigned to different groups, are an extremely reliable way to get closer to the truth. Given this difference, how much should we rely on mining Big Data to answer scientific questions? Are randomized experiments necessarily too difficult, expensive or unethical to conduct, or are these fixable problems? Does the human desire for certainty predispose us to an irrational dislike of randomized experiments, one that might be holding science back?