Evaluating the Alignment of a Data Analysis between Analyst and Audience
Abstract
A challenge that data analysts face is building a data analysis that is useful for a given consumer. Previously, we defined a set of principles for describing data analyses that can be used to create a data analysis and to characterize the variation between analyses. Here, we introduce a concept that we call the alignment of a data analysis between the data analyst and a consumer. We define a successfully aligned data analysis as the matching of principles between the analyst and the consumer for whom the analysis is developed. In this paper, we propose a statistical model for evaluating the alignment of a data analysis and describe some of its properties. We argue that this framework provides a language for characterizing alignment and can be used as a guide for practicing data scientists and students in data science courses for how to build better data analyses.
Cite
@article{arxiv.2312.07616,
title = {Evaluating the Alignment of a Data Analysis between Analyst and Audience},
author = {Lucy D'Agostino McGowan and Roger D. Peng and Stephanie C. Hicks},
journal= {arXiv preprint arXiv:2312.07616},
year = {2023}
}