在过去的几十年中，我们对宇宙的认识已经完全改变，因为我们已经确认存在长久以来被猜想的天体（黑洞，中子星，引力波，系外行星）并发现了全新的天体（暗物质，伽马射线爆发） ，暗能量，霍金辐射）。这些发现中的许多，以及当前大多数的天文学探索，都涉及天文学家和统计科学家之间的密切合作。近期和即将推出的望远镜，既有地基的（巨型麦哲伦望远镜（GMT），大型天气观测望远镜（LSST）等），又有天基的（过境外行星观测（TESS），詹姆斯·韦伯太空望远镜（JWST）等）。 ）每天要产生TB级的新数据，这就需要采用全新的统计分
Our understanding of the universe has been entirely transformed in the past few decades as we have confirmed the existence of long-conjectured celestial objects (black holes, neutron stars, gravity waves, exoplanets) and discovered entirely new ones (dark matter, gamma ray bursts, dark energy, Hawking radiation). Many of these discoveries, and most of the current exploration in astronomy, involve close collaboration between astronomers and statistical scientists. Recent and upcoming telescopes, both ground-based (Giant Magellan Telescope (GMT), Large Synoptic Survey Telescope (LSST), etc.) and space-based (Transiting Exoplanet Survey (TESS), James Webb Space Telescope (JWST), etc.), are generating terabytes a day of new data that call for entirely new methods of statistical analysis to support scientific inquiry, and extensions of existing methods. Important statistical tools in this area include Bayesian time series analysis, stochastic processes, and multivariate statistics, and compressed sensing.