Date: Fri, 11 Mar 2016 16:00:00 +0000
<p>Today on Data Skeptic, <a href="https://www.eleceng.adelaide.edu.au/personal/dabbott/wiki/index.php/Lachlan_J._Gunn"> Lachlan Gunn</a> joins us to discuss his recent paper <a href="http://arxiv.org/abs/1601.00900">Too Good to be True</a>. This paper highlights a somewhat paradoxical / counterintuitive fact about how unanimity is unexpected in cases where perfect measurements cannot be taken. With large enough data, some amount of error is expected.</p> <p>The "Too Good to be True" paper highlights three interesting examples which we discuss in the podcast. You can also watch a lecture from Lachlan on this topic via youtube <a href="https://www.youtube.com/watch?v=Uz6xUjJHTII">here</a>.</p>
