The AstroStat Slog » Jargon http://hea-www.harvard.edu/AstroStat/slog Weaving together Astronomy+Statistics+Computer Science+Engineering+Intrumentation, far beyond the growing borders Fri, 09 Sep 2011 17:05:33 +0000 en-US hourly 1 http://wordpress.org/?v=3.4 language barrier http://hea-www.harvard.edu/AstroStat/slog/2008/language-barrier/ http://hea-www.harvard.edu/AstroStat/slog/2008/language-barrier/#comments Wed, 13 Feb 2008 20:41:32 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2008/language-barrier/ Last week, I was at Tufts colloquium and happened to have a conversation with a computer scientist about density based clustering. I understood density as probabilistic density and was recollecting a paper by Fraley and Raftery (Model-Based Clustering, Discriminant Analysis, and Density Estimation, JASA, 2002, 97, p.458) and other similar papers I saw in engineering journals like IEEE transactions. For a few moments, I felt uncomfortable and she explained that density meant “how dense observations are.” Density based clustering was meant to be distance based clustering, like k-means, minimum spanning tree, most likely nonparametric approaches.

Although words are same, the first impression and their usage is quite different from society to society (even among statisticians). One word I’m very reluctant to use both to astronomers and statisticians is model. I’m quite confused at the reactions from both sides. To clarify meanings, implications, or intentions, some clever adjectives must accompany these common words; however, once one gets used to these jargons, adjectives are felt redundant to your fellow scientists/colleagues, whereas the other gets lost and seeks explanation of the usage by related examples and backgrounds.

Not only simple words, like model and density, there are more jargons requires inter-disciplinary semantic experts. Yet, patience of explaining and open-mindedness would easily assist to get over language barriers in any interdisciplinary works.

[ Would you mind sharing your experience of any language barrier? ]

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model vs model http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/ http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/#comments Fri, 05 Oct 2007 17:38:23 +0000 vlk http://hea-www.harvard.edu/AstroStat/slog/2007/model-vs-model/ As Alanna pointed out, astronomers and statisticians mean different things when they say “model”. To complicate matters, we have also started to use another term called “data model”.

First, there is the physical model, which could mean either our understanding of what processes operate on a source (the physics part, usually involving PDEs), or the mathematical function that describes the emission as a function of observables like location, time, or energy (the astronomy part, usually the shape of the spectrum, or the time evolution in a light curve, etc.)

The data model on the other hand describes the organization of the observation. It is this which tells us that there is a fundamental difference between an effective area and a response matrix, and conversely, that the point spread function and the line response function are the same beast. This kind of thing, which I suppose is a computer science oriented view of the contents of a file, is crucial for implementing and running something like the Virtual Observatory.

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[ArXiv] A Lecture Note, June 17, 2007 http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-june-17-2007/ http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-june-17-2007/#comments Mon, 18 Jun 2007 19:06:55 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2007/arxiv-june-17-2007/ From arxiv/astro-ph:0706.1988,
Lectures on Astronomy, Astrophysics, and Cosmology looks helpful to statisticians who like to know astronomy, astrophysics, and cosmology. The lecture note starts from introducing fundamentals of astronomy, UNITS!!!, and its history. It also explains astronomical measures such as distances and their units, luminosity, and temperature; HR diagram (astronomers’ summary diagram); stellar evolution; and relevant topics in cosmology. At least, a third of the article will be useful to grasp a rough idea of astronomy as a scientific subject beyond colorful pictures. Statisticians who are keen to cosmology are recommended to read beyond.

This is not a high energy lecture note; therefore, statisticians interested in high energy are encouraged to visit Astro Jargon for Statisticians and CHASC.

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Categories http://hea-www.harvard.edu/AstroStat/slog/2007/categories/ http://hea-www.harvard.edu/AstroStat/slog/2007/categories/#comments Fri, 25 May 2007 15:51:43 +0000 vlk http://hea-www.harvard.edu/AstroStat/slog/2007/categories/ It seems to be necessary to devise a good system of categories beforehand with wordpress, because plain tags are not (yet?) implemented. Categories can only be defined by the admin, so it is useful to have as comprehensive a list as possible. I suggest the following set:

(Edited slightly to reorganize)

Meta (about the site, the software, etc)
News
(conferences, deadlines, workshops, schools, etc.)
Nuggets
(research reports, new algorithms, etc.)
CHASC
(about CHASC)
Quotes
Jargon
Bad AstroStat

Astro (primarily Astronomy or Astrophysics oriented posts)
Astro > High-Energy
Astro > High-Energy > X-ray
Astro > High-Energy > gamma-ray
Astro > Optical
Astro > Physics
Astro > Stars
Astro > Galaxies
Astro > Objects

Stat (primarily Statistics oriented posts)
Stat > Bayesian
Stat > Frequentist
Stat > Fitting
Stat > Uncertainty
Stat > MC
Stat > MC > MCMC

Algorithms
Imaging
Spectral
Timing
Data Processing
Languages

Corrections and additions welcome!

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Statistics Jargon for Astronomers http://hea-www.harvard.edu/AstroStat/slog/2007/statistics-jargons-for-astronomers/ http://hea-www.harvard.edu/AstroStat/slog/2007/statistics-jargons-for-astronomers/#comments Mon, 29 Jan 2007 06:19:20 +0000 hlee http://hea-www.harvard.edu/AstroStat/slog/2007/statistics-jargons-for-astronomers/ The Statistics Jargon for Astronomers has revived (Jan. 2007) but now, it is barely breathing. Effortlessly search engines and Internet encyclopedia provide details on statistical terminologies for astronomers, which cast the largest difficulty on this jargon website. We urge both astronomers and statisticians’ contributions for compiling this lexicon and their discussions on both subjects.

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