论文标题
统计和数据科学合作的内容：QQQ框架
The Content of Statistics and Data Science Collaborations: the QQQ Framework
论文作者
论文摘要
对于当今的应用统计学家和数据科学家来说，协作是现实。统计学家（和数据科学家）可以与学术领域，行业以及政府和非政府组织的领域专家合作。因此，统计学家必须开发协作技能和技术。为此，我们推进了一个称为定性定量质量质量（QQQ，发音为“ Q-Q-Q”）方法的框架，以系统化统计协作的内容。 QQQ方法明确强调了项目定性背景的重要性以及定量发现的定性解释。我们将解释QQQ方法及其每个组件，以应用于统计学和数据科学咨询和协作。我们提供了实施方法的每个阶段的指导，并介绍了评估QQQ方法开始合作者的有效性的数据。
For today's applied statisticians and data scientists, collaboration is a reality. Statisticians (and data scientists) may collaborate with domain experts across academic fields, industry sectors, and governmental and non-governmental organizations. Thus, statisticians must develop skills and techniques for collaboration. To this end, we advance a framework called the Qualitative-Quantitative-Qualitative (QQQ, pronounced "Q-Q-Q") approach to systematize the content of statistical collaborations. The QQQ approach explicitly emphasizes the importance of the qualitative context of a project, as well as the qualitative interpretation of quantitative findings. We explain the QQQ approach and each of its components as applied to statistics and data science consultations and collaborations. We provide guidance for implementing each stage of the approach and present data evaluating the effectiveness of teaching the QQQ approach to beginning collaborators.
