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Statistics for big data: A perspective

Peter Bühlmann and Sara van de Geer

Statistics & Probability Letters, 2018, vol. 136, issue C, 37-41

Abstract: We look at the role of statistics in data science. Two statisticians, two views. Besides the need of developing appropriate concepts, methodology and algorithms, the first one makes a case for validation and carefully designed simulation studies, while the second one writes that a mathematical underpinning of methods is fundamental. Both views converge to the same point: there should be more room for publishing negative findings.

Keywords: Heterogeneity; Lasso; Learning theory; Negative results; Replicability; Reproducibility (search for similar items in EconPapers)
Date: 2018
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Handle: RePEc:eee:stapro:v:136:y:2018:i:c:p:37-41