Výsledky vyhledávání - "Gibbs Alison L"

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Computational Skills by Stealth in Secondary School Data Science

Autor: Burr, Wesley, Chevalier, Fanny, Collins, Christopher, Gibbs, Alison L, Ng, Raymond, Wild, Chris

The unprecedented growth in the availability of data of all types and qualities and the emergence of the field of data science has provided an impetus to finally realizing the implementation of the full breadth of the Nolan and Temple Lang proposed i

Externí odkaz: http://arxiv.org/abs/2010.07017

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Akademický článek

Bioactive oat β-glucan reduces LDL cholesterol in Caucasians and non-Caucasians

Autor: Wolever Thomas MS, Gibbs Alison L, Brand-Miller Jennie, Duncan Alison M, Hart Valerie, Lamarche Benoît, Tosh Susan M, Duss Ruedi

Publikováno v: Nutrition Journal, Vol 10, Iss 1, p 130 (2011)

Abstract Background There is increasing global acceptance that viscous soluble fibers lower serum LDL cholesterol (LDL-C), but most evidence for this comes from studies in Caucasians. To see if oat β-glucan lowers LDL-C in Caucasians and non-Caucasi

Externí odkaz: https://doaj.org/article/b97f05332fe2412ea0ac5e3b515297d7

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Akademický článek

Equivalent glycemic load (EGL): a method for quantifying the glycemic responses elicited by low carbohydrate foods

Autor: Spolar Matt, Gibbs Alison L, Wolever Thomas MS, Hitchner Elinor V, Heimowitz Colette

Publikováno v: Nutrition & Metabolism, Vol 3, Iss 1, p 33 (2006)

Abstract Background Glycemic load (GL) is used to quantify the glycemic impact of high-carbohydrate (CHO) foods, but cannot be used for low-CHO foods. Therefore, we evaluated the accuracy of equivalent-glycemic-load (EGL), a measure of the glycemic i

Externí odkaz: https://doaj.org/article/24ce703776514112bf480f85eb92876f

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On choosing and bounding probability metrics

Autor: Gibbs, Alison L., Su, Francis Edward

Publikováno v: International Statistical Review (2002), vol. 70, number 3, 419-435.

When studying convergence of measures, an important issue is the choice of probability metric. In this review, we provide a summary and some new results concerning bounds among ten important probability metrics/distances that are used by statistician

Externí odkaz: http://arxiv.org/abs/math/0209021

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