Introducing Undergraduates to Concepts of Survey Data Analysis

IF 2.2 Q3 Social Sciences Journal of Statistics Education Pub Date : 2020-01-02 DOI:10.1080/10691898.2020.1720552
Pamela S. Fellers, Shonda Kuiper
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引用次数: 9

Abstract

Abstract Increasingly students, particularly those in the social sciences, work with survey data collected through a more complex sampling method than a simple random sample. Failing to understand how to properly approach survey data can lead to inaccurate results. In this article, we describe a series of online data visualization applications and corresponding student lab activities designed to help students and teachers of statistics better understand survey design and analysis. The introductory and advanced materials presented are designed to focus on a conceptual understanding of survey data and provide an awareness of the challenges and potential misuse of survey data. Suggestions and examples of how to incorporate these materials are also included. Supplementary materials for this article are available online.
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向本科生介绍调查数据分析的概念
越来越多的学生,特别是社会科学专业的学生,通过更复杂的抽样方法收集调查数据,而不是简单的随机抽样。不了解如何正确处理调查数据可能导致不准确的结果。在本文中,我们描述了一系列在线数据可视化应用程序和相应的学生实验活动,旨在帮助统计专业的学生和教师更好地理解调查设计和分析。介绍和高级材料的设计重点是对调查数据的概念理解,并提供对调查数据的挑战和潜在滥用的认识。还包括如何合并这些材料的建议和示例。本文的补充材料可在网上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Statistics Education
Journal of Statistics Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
12 weeks
期刊介绍: The "Datasets and Stories" department of the Journal of Statistics Education provides a forum for exchanging interesting datasets and discussing ways they can be used effectively in teaching statistics. This section of JSE is described fully in the article "Datasets and Stories: Introduction and Guidelines" by Robin H. Lock and Tim Arnold (1993). The Journal of Statistics Education maintains a Data Archive that contains the datasets described in "Datasets and Stories" articles, as well as additional datasets useful to statistics teachers. Lock and Arnold (1993) describe several criteria that will be considered before datasets are placed in the JSE Data Archive.
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