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Illustrating Randomness in Statistics Courses With Spatial Experiments

机译:用空间实验说明统计课程中的随机性

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Understanding the concept of randomness is fundamental for students in introductory statistics courses, but the notion of randomness is deceivingly complex, so it is often emphasized less than the mechanics of probability and inference. The most commonly used classroom tools to assess students' production or perception of randomness are binary choices, such as coin tosses, and number sequences, such as dice rolls. The field of psychology has a long history of research on random choice, and we have replicated some experiments that support results seen there regarding the collective distribution of individual choices in spatial geometries. The data from these experiments can easily be incorporated into the undergraduate classroom to visually illustrate the concepts of random choice, complete spatial randomness (CSR), and Poisson processes. Furthermore, spatial statistics classes can use this point pattern data in exploring hypothesis tests for CSR along with simulation. To foster student engagement, it is simple to collect additional data from students to assess agreement with existing data or to develop related, unique experiments. All R code and data to duplicate results are provided.
机译:理解随机性的概念是介绍性统计课程的学生的基础,但随机性的概念是蔑视复杂的,因此通常强调低于概率和推理的机制。评估学生的生产或对随机性感知的最常用的课堂工具是二进制选择,例如硬币折叠和数量序列,例如骰子卷。心理学领域具有悠久的随机选择研究历史,我们已经复制了一些实验,即支持存在关于空间几何形状中各个选择的集体分布的结果。这些实验的数据可以很容易地纳入本科教室,以便在视觉上说明随机选择,完整的空间随机性(CSR)和泊松过程的概念。此外,空间统计类可以使用此点模式数据来探索CSR的假设测试以及模拟。为了培养学生参与,它很简单地收集学生的其他数据,以评估与现有数据的协议或开发相关的独特实验。提供所有R代码和数据到重复结果。

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