Six Maxims of Statistical Acumen for Astronomical Data Analysis

被引:0
作者
Tak, Hyungsuk [1 ]
Chen, Yang [2 ]
Kashyap, Vinay L. [3 ]
Mandel, Kaisey S. [4 ,5 ,6 ]
Meng, Xiao-Li [7 ]
Siemiginowska, Aneta [3 ]
van Dyk, David A. [8 ]
机构
[1] Penn State Univ, Inst Computat & Data Sci, Dept Stat Astron & Astrophys, University Pk, PA 16802 USA
[2] Univ Michigan, Dept Stat, Ann Arbor, MI 48109 USA
[3] Harvard Smithsonian Ctr Astrophys, Cambridge, MA 02138 USA
[4] Univ Cambridge, Inst Astron, Cambridge CB3 0HA, England
[5] Univ Cambridge, Kavli Inst Cosmol, Cambridge CB3 0HA, England
[6] Univ Cambridge, Stat Lab, DPMMS, Wilberforce Rd, Cambridge CB3 0WB, England
[7] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA
[8] Imperial Coll London, Dept Math, Stat Sect, London SW7 2AZ, England
基金
欧盟地平线“2020”; 英国工程与自然科学研究理事会; 美国国家科学基金会;
关键词
TIME DELAYS; LINEAR-REGRESSION; UPPER LIMITS; STOCHASTIC VARIABILITY; OPTICAL VARIABILITY; MEASUREMENT ERRORS; LIKELIHOOD RATIO; HUBBLE CONSTANT; ENERGY-SPECTRA; MALMQUIST BIAS;
D O I
10.3847/1538-4365/ad8440
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
The acquisition of complex astronomical data is accelerating, especially with newer telescopes producing ever more large-scale surveys. The increased quantity, complexity, and variety of astronomical data demand a parallel increase in skill and sophistication in developing, deciding, and deploying statistical methods. Understanding limitations and appreciating nuances in statistical and machine learning methods and the reasoning behind them is essential for improving data-analytic proficiency and acumen. Aiming to facilitate such improvement in astronomy, we delineate cautionary tales in statistics via six maxims, with examples drawn from the astronomical literature. Inspired by the significant quality improvement in business and manufacturing processes by the routine adoption of Six Sigma, we hope the routine reflection on these six maxims will improve the quality of both data analysis and scientific findings in astronomy.
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页数:13
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共 124 条
  • [1] Abbott B. P., 2016, PHYSICAL REVIEW LETTERS, V116, P61102, DOI [10.1103/PhysRevLett.116.061102, DOI 10.1103/PHYSREVLETT.116.061102]
  • [2] Planck 2015 results XVII. Constraints on primordial non-Gaussianity
    Ade, P. A. R.
    Aghanim, N.
    Arnaud, M.
    Arrojam, F.
    Ashdown, M.
    Aumont, J.
    Baccigalupi, C.
    Ballardini, M.
    Banday, A. J.
    Barreiro, R. B.
    Bartolo, N.
    Basak, S.
    Battaner, E.
    Benabed, K.
    Benoit, A.
    Benoit-Levy, A.
    Bernard, J. -P.
    Bersanelli, M.
    Bielewicz, P.
    Bock, J. J.
    Bonaldi, A.
    Bonavera, L.
    Bond, J. R.
    Borrill, J.
    Bouchet, F. R.
    Boulanger, F.
    Bucher, M.
    Burigana, C.
    Butler, R. C.
    Calabrese, E.
    Cardoso, J. -F.
    Catalano, A.
    Challinor, A.
    Chamballu, A.
    Chiang, H. C.
    Christensen, P. R.
    Church, S.
    Clements, D. L.
    Colombi, S.
    Colombo, L. P. L.
    Combet, C.
    Couchot, F.
    Coulais, A.
    Crill, B. P.
    Curto, A.
    Cuttaia, F.
    Danese, L.
    Davies, R. D.
    Davis, R. J.
    de Bernardis, P.
    [J]. ASTRONOMY & ASTROPHYSICS, 2016, 594
  • [3] Prediction of Solar Eruptions Using Filament Metadata
    Aggarwal, Ashna
    Schanche, Nicole
    Reeves, Katharine K.
    Kempton, Dustin
    Angryk, Rafal
    [J]. ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 2018, 236 (01)
  • [4] NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION
    AKAIKE, H
    [J]. IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) : 716 - 723
  • [5] Linear regression for astronomical data with measurement errors and intrinsic scatter
    Akritas, MG
    Bershady, MA
    [J]. ASTROPHYSICAL JOURNAL, 1996, 470 (02) : 706 - 714
  • [6] Assessment of stochastic and deterministic models of 6304 quasar lightcurves from SDSS Stripe 82
    Andrae, R.
    Kim, D.-W.
    Bailer-Jones, C.A.L.
    [J]. 1600, EDP Sciences (554):
  • [7] Measurement Errors and Scaling Relations in Astrophysics: A Review
    Andreon, Stefano
    Hurn, Merilee
    [J]. STATISTICAL ANALYSIS AND DATA MINING, 2013, 6 (01) : 15 - 33
  • [8] [Anonymous], 1985, MAKING DECISIONS
  • [9] When to use the Bonferroni correction
    Armstrong, Richard A.
    [J]. OPHTHALMIC AND PHYSIOLOGICAL OPTICS, 2014, 34 (05) : 502 - 508
  • [10] Stratified learning: A general-purpose statistical method for improved learning under covariate shift
    Autenrieth, Maximilian
    van Dyk, David A.
    Trotta, Roberto
    Stenning, David C.
    [J]. STATISTICAL ANALYSIS AND DATA MINING, 2024, 17 (01)