LRP2020: Astrostatistics in Canada
Gwendolyn Eadie, Arash Bahramian, Pauline Barmby, Radu Craiu, Derek, Bingham, Ren\'ee Hlo\v{z}ek, JJ Kavelaars, David Stenning, Samantha, Benincasa, Guillaume Thomas, Karun Thanjavur, Jo Bovy, Jan Cami, Ray, Carlberg, Sam Lawler, Adrian Liu, Henry Ngo, Mubdi Rahman, Michael Rupen

TL;DR
This paper reviews the growth of astrostatistics and astroinformatics, highlights Canada's limited role, and recommends strategies to enhance interdisciplinary training and collaboration in these fields over the next decade.
Contribution
It provides a survey-based analysis of Canadian astronomers' training needs and offers actionable recommendations to strengthen astrostatistics and astroinformatics in Canada.
Findings
Astronomers recognize the importance of statistical methods.
There is a lack of formal training in astrostatistics.
Recommendations for improving interdisciplinary education and collaboration.
Abstract
(Abridged from Executive Summary) This white paper focuses on the interdisciplinary fields of astrostatistics and astroinformatics, in which modern statistical and computational methods are applied to and developed for astronomical data. Astrostatistics and astroinformatics have grown dramatically in the past ten years, with international organizations, societies, conferences, workshops, and summer schools becoming the norm. Canada's formal role in astrostatistics and astroinformatics has been relatively limited, but there is a great opportunity and necessity for growth in this area. We conducted a survey of astronomers in Canada to gain information on the training mechanisms through which we learn statistical methods and to identify areas for improvement. In general, the results of our survey indicate that while astronomers see statistical methods as critically important for their…
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Taxonomy
TopicsData Analysis with R
