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MSNBC The ReidOut July 6, 2024



i think what joy reid did frankly is the issue that happens to black conservatives all the time. where somehow we re less black than black democrats. first of all, i ll tell you and i ll tell joy reid and anyone else who wants to hear it, i grew up in brooklyn, new york, in the inner city, in a single parent household. i am a black man. i m also a republican. the republican congressman you just heard, byron donalds of florida, who got a bunch of votes for speaker, joins me in studio tonight. meanwhile, kevin mccarthy and his far right overlords are off and running with an extreme agenda. and normalizing people like marjorie taylor greene and paul gosar. while punishing lawmakers like adam schiff, ilhan omar, and eric swalwell, who joins me in just a moment. plus, my pal and colleague, chris hayes, is going to help me make a big announcement tonight. you do not want to miss it. we begin with the extreme republican agenda taking shape in the u.s. house of representa ....

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MSNBCW All July 2, 2024



very important, that s the winner of the week. brian tyler cohen, brittany packnett cunningham, thank you, that is tonight s reidout. all in with chris hayes starts now. ts now. tonight on all in. donald trump cannot make public comments about known or foreseeable witnesses in a case. the trump gag order is upheld in a major court decision, with big implications for the timing of the coup trial. it makes that march 4th trial date increasingly farm. as trump s codefendant in georgia helps make cases in four other states. the please lower your hand instead your true and correct the legal name. kenneth john chesebro. then the state of texas threatens to jail doctors for following court orders on a emergency abortion. this is the attorney general saying that she should be the one practicing medicine rather than the physicians in his state. and how in the world will be right wing spin machine handle another and unambiguously good jobs report? when i m going ....

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"Decisions, decisions, decisions in an uncertain environment" by Noel Cressie

Decision-makers abhor uncertainty, and it is certainly true that the less there is of it the better. However, recognizing that uncertainty is part of the equation, particularly for deciding on environmental policy, is a prerequisite for making wise decisions. Even making no decision is a decision that has consequences, and using the presence of uncertainty as the reason for failing to act is a poor excuse. Statistical science is the science of uncertainty, and it should play a critical role in the decision-making process. This opinion piece focuses on the summit of the knowledge pyramid that starts from data and rises in steps from data to information, from information to knowledge, and finally from knowledge to decisions. Enormous advances have been made in the last 100 years ascending the pyramid, with deviations that have followed different routes. There has generally been a healthy supply of uncertainty quantification along the way but, in a rush to the top, where the decisions are ....

Bayesian Model Averaging , Xpected Posterior Loss , Loss Function , Osterior Distribution ,

"Optimal Spatial Prediction for Non-negative Spatial Processes Using a " by Noel Cressie, Alan R. Pearse et al.

A major component of inference in spatial statistics is that of spatial prediction of an unknown value from an underlying spatial process, based on noisy measurements of the process taken at various locations in a spatial domain. The most commonly used predictor is the conditional expectation of the unknown value given the data, and its calculation is obtained from assumptions about the probability distribution of the process and the measurements of that process. The conditional expectation is unbiased and minimises the mean-squared prediction error, which can be interpreted as the unconditional risk based on the squared-error loss function. Cressie [4, p. 108] generalised this approach to other loss functions, to obtain spatial predictors that are optimal (i.e., that minimise the unconditional risk) but not necessarily unbiased. This chapter is concerned with spatial prediction of processes that take non-negative values, for which there is a class of loss functions obtained by adaptin ....

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