Design principles for data analysis


Details
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SYNOPSIS
Dr. Stephanie Hicks will join us to talk about design thinking – the problem-solving process to understand the people for whom a data analysis product is being designed – and how the choices a data analyst makes affect the experience of the consumer.
Title: Design Principles for Data Analysis
Abstract: The data revolution has led to an increased interest in the practice of data analysis. While much has been written about statistical thinking, a complementary form of thinking that appears in the practice of data analysis is design thinking -- the problem-solving process to understand the people for whom a solution is being designed. For a given problem, there can be significant or subtle differences in how a data analyst (or producer of a data analysis) constructs, creates, or designs a data analysis, including differences in the choice of methods, tooling, and workflow. These choices can affect the data analysis products themselves and the experience of the consumer of the data analysis. Therefore, the role of a producer can be thought of as designing the data analysis with a set of design principles. Here, we introduce design principles for data analysis and discuss some case studies where they were used in the classroom to characterize data analyses.
Relevant preprint: [https://arxiv.org/abs/2103.05689](https://urldefense.com/v3/https://arxiv.org/abs/2103.05689;!!HXCxUKc!htOZS1uCBo-VVA0L8WNW0s9jv2GJW74ggOL2QKX3UkkfIOWFpVim9jpHPGMPg6gP$)
PRESENTER
Dr. Stephanie Hicks, assistant professor in the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health, is also giving a virtual seminar titled: "Scalable statistical methods and software for single-cell data science" in the Department of Biochemistry and Molecular Biology on Thursday, April 14, at 11a (email janani[AT]msu[DOT]edu for this Zoom link). One of the focuses of Dr. Hicks’ group is the analysis of high-throughput biological data, including single-cell RNA-seq data.
About RLEL
R-Ladies East Lansing (RLEL) is a chapter of R-Ladies Global, an organization whose mission is to promote gender diversity in the R programming community. All genders are welcome at RLEL meetups, and participants must follow the R-Ladies code of conduct.

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Design principles for data analysis