RUI: Collaborative Research: Sample Size Bias in Judgments of Averages

这个项目关注的是一种被称为样本量偏差的数量认知现象，这种现象发生在人们对平均数做出判断时。具体地说，当集合中的项目数量增加时，人们会判断平均值更大。例如，一组十个数字的平均值被判断为大于五个数字的平均值--即使这两个集合具有相同的平均值。但在风险等概念性维度上也会出现样本量偏差。例如，10个人的平均心脏病发作风险被判断为比5个人的平均心脏病发作风险更大。这个项目的核心是一系列的实证研究，在这些研究中，不同阶层的人在各种情况下判断几种平均值。这些研究有两个目的。首先是测试一种理论，该理论假设集合大小自动激活大脑中对大小的模拟表示，而这反过来又会影响对平均值的表示和判断。第二个是看样本量偏差是否会影响对平均值的其他类型的判断，包括对自己经验和行为的判断。这项工作之所以重要，原因有很多。首先，正在测试的理论有可能帮助整合样本大小偏差与来自不同研究领域的类似现象，包括判断和决策、知觉和定量认知的神经科学。其次，这项研究将有助于识别人们对平均值的判断可能反映样本大小偏差的现实世界背景。例如，调查经常要求人们判断他们或他们的同龄人的平均或典型情况(例如，他们每年平均使用卫生服务的次数)。重要的是要知道这样的判断是否可能是系统性的偏见，以及如何纠正这种偏见。最后，该项目将为加州州立大学、弗雷斯诺州立大学和阿巴拉契亚州立大学的不同本科生和硕士学生提供高质量的研究培训和经验。这反过来将为他们在认知和社会心理学、判断和决策以及管理科学等不同领域的博士学习中取得成功做好准备。

This project focuses on a phenomenon of quantitative cognition called sample size bias, which occurs when people make judgments of averages. Specifically, as the number of items in a set increases, people judge the average to be greater. For example, the average of a set of ten numbers is judged to be greater than the average of five numbers -- even when the two sets have the same average. But sample size bias also occurs for conceptual dimensions such as risk. For example, the average heart-attack risk of ten people is judged to be greater than the average heart-attack risk of five people. The core of this project is a series of empirical studies in which a cross-section of people judge several kinds of averages under a variety of conditions. These studies have two purposes. The first is to test a theory that assumes that set size automatically activates an analog representation of magnitude in the brain, which in turn affects the representation and judgment of the average. The second is to see whether the sample size bias affects other kinds of judgments about averages, including judgments about one's own experience and behavior.This work is important for a number of reasons. First, the theory being tested has the potential to help integrate sample size bias with similar phenomena from distinct areas of research including judgment and decision making, perception, and the neuroscience of quantitative cognition. Second, this research will help identify real-world contexts in which people's judgments of averages are likely to reflect sample size bias. For example, surveys often ask people to make judgments about what is average or typical for them or their peers (e.g., the average number of times they use health services per year). It is important to know whether such judgments are likely to be systematically biased and how such biases might be corrected. Finally, this project will provide high quality research training and experience to a diverse group of undergraduate and master's-level students at California State University, Fresno and Appalachian State University. This in turn will prepare them to succeed in doctoral studies in any of a variety of areas, cognitive and social psychology, judgment and decision making, and management science.