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welcome back to the channel in the previous episode we discussed that in the forecasting competition introduced there the expert who correctly inferred the true underlying distribution for each test day and submitted the distributions expected value as FairPoint forecast of the day lost to naive forecasters when the error metric was anything but mean squared error within the next several minutes and using Concepts from the field of Bayesian decision making under uncertainty I will explain the main reason she Rings under mean squirter lets understand this by focusing on what happens in the first test day the organizer has the true underlying distribution for the vertical axis plausible values and horizontal axis the associated probability densities has sampled a single point from it but that point which only presents the true value for the first test day is not shared with the participants they are asked to submit their forecasts for the day the expert has correctly inferred the underl