6,155,282 research outputs found
Curriculum Guidelines for Undergraduate Programs in Data Science
Get PDFThe Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
Robust Statistics
Get PDFIn lieu of an abstract, here is the entry\u27s first paragraph:
Robust statistics are procedures that maintain nominal Type I error rates and statistical power in the presence of violations of the assumptions that underpin parametric inferential statistics. Since George Box coined the term in 1953, research on robust statistics has centered on the assumption of normality, although the violation of other parametric assumptions (e.g., homogeneity of variance) has their own implications for the accuracy of parametric procedures. This entry looks at the importance of robust statistics in educational and social science research and explains the robustness argument. It then describes robust descriptive statistics, their inferential extensions, and two common resampling procedures that are robust alternatives to classic parametric methods
On Infinite Quon Statistics and "Ambiguous" Statistics
Get PDFWe critically examine a recent suggestion that "ambiguous" statistics is
equivalent to infinite quon statistics and that it describes a dilute,
nonrelativistics ideal gas of extremal black holes. We show that these two
types of statistics are different and that the description of extremal black
holes in terms of "ambiguous" statistics cannot be applied.Comment: Latex, 9 pages, no figures, to appear in Mod.Phys.Lett.
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