Howdy. Folks! Suppose X is normally distributed according to mean M and variance 1.We make an observation of X.How should we estimate M? If you're thinking "just take the mean of observations", you're wrong!Or, at least, you're missing a bigger, more surprising story. We'll kickoff this semester's MSAIL with the story of Stein's Paradox a counter-intuitive result in the statistics behind Machine Learning. We'll meet:     EECS 3433, Wednesday, 2016-01-18, 19:00-20:00.Afterward, we'll have the room reserved for an additional hourfor informal discussion, coding, and socializing. We lookforward to seeing you there! Totally optionally, for those interested, check out the following links!these notes from UWashington on "admissibility"Wikipedia's article "Stein's Paradox"  Cheers,MSAIL