Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Jun, Eunice"'
Statistical models should accurately reflect analysts' domain knowledge about variables and their relationships. While recent tools let analysts express these assumptions and use them to produce a resulting statistical model, it remains unclear what
Externí odkaz:
http://arxiv.org/abs/2310.16262
Autor:
Misback, Edward, Chan, Caleb C., Saiki, Brett, Jun, Eunice, Tatlock, Zachary, Panchekha, Pavel
In recent years, researchers have proposed a number of automated tools to identify and improve floating-point rounding error in mathematical expressions. However, users struggle to effectively apply these tools. In this paper, we work with novices, e
Externí odkaz:
http://arxiv.org/abs/2305.10599
Publikováno v:
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI '23), April 23-28, 2023, Hamburg, Germany. ACM, New York, NY, USA
Multiverse analysis, a paradigm for statistical analysis that considers all combinations of reasonable analysis choices in parallel, promises to improve transparency and reproducibility. Although recent tools help analysts specify multiverse analyses
Externí odkaz:
http://arxiv.org/abs/2210.03804
Proper statistical modeling incorporates domain theory about how concepts relate and details of how data were measured. However, data analysts currently lack tool support for recording and reasoning about domain assumptions, data collection, and mode
Externí odkaz:
http://arxiv.org/abs/2201.02705
Data analysis requires translating higher level questions and hypotheses into computable statistical models. We present a mixed-methods study aimed at identifying the steps, considerations, and challenges involved in operationalizing hypotheses into
Externí odkaz:
http://arxiv.org/abs/2104.02712
Autor:
Jun, Eunice, Daum, Maureen, Roesch, Jared, Chasins, Sarah E., Berger, Emery D., Just, Rene, Reinecke, Katharina
Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific statistical tests and then perform API calls with functions and param
Externí odkaz:
http://arxiv.org/abs/1904.05387
A qualitative lab study exploring cognitive heuristics while making decisions under model uncertainty
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7de72a40ac7b15d5cfae485098ef174
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Computer Graphics Forum. Jun2019, Vol. 38 Issue 3, p67-78. 12p. 13 Diagrams, 1 Graph.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.