By Prakash Nair
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Extra info for 30 Strategies for Education Reform
These have the solution mentioned. 4 Data fitting for EV 21 three prospects predicted by the probability vectors are off from the observed CEs. For instance, for the first prospect the predicted CE is 4p1, so that the probability vector is off by |4p1 À 2|, with squared distance (4p1 À 2)2. We similarly take the squared distances for the other two prospects, take the average of these three squared distances, and then take its square root. It leads to the following distance formula: sﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ ð4p1 À 2Þ2 þ ð3p2 À 1Þ2 þ ð1:5 À 3p1 À 3p3 Þ2 : 3 The distance has money as its unit and can be interpreted as the amount by which the model is off in dollars.
For a constant prospect there is no uncertainty about the outcome, and we often denote the prospect simply as that outcome. For example, we write 100 instead of (s1:100, s2:100, s3:100). 2, the prospect denoted 0 is constant, yielding 0 profit whatever the copper price. For a given prospect denoted E1x1Á Á ÁEnxn, the events Ej are called the outcome events. These are the payoff-relevant events. It is implicitly assumed for each prospect that the outcome events are exhaustive and mutually exclusive.
2, the prospect denoted 0 is constant, yielding 0 profit whatever the copper price. For a given prospect denoted E1x1Á Á ÁEnxn, the events Ej are called the outcome events. These are the payoff-relevant events. It is implicitly assumed for each prospect that the outcome events are exhaustive and mutually exclusive. That is, they partition the state space S. Exactly one of them is true (contains the true state) and the others are not true. If the partition (E1,. ,En) is understood, we sometimes suppress the events and write, briefly, (x1,.
30 Strategies for Education Reform by Prakash Nair