### Table E-2.3. Probability distributions of transport parameters used in Monte Carlo model.

### TABLE 1. Weekly Average Rainfall and Evapotranspiration

### Table 1. Full-Sample Estimates of Impact of IMF Programs on Market Access

2000

"... In PAGE 21: ... We are also interested in the differential effects of different types of conditionality. In column (1) of Table1 , we show the results of the probit relating the decision to... ..."

### Table 1 Probability Distribution of Returns

"... In PAGE 4: ...2. Table1 lists the probability distribution of returns f(r|i) as well as the expected return. The socially desirable investment strategy is is.... ..."

### Table 1: Comparison of the probability distribution of the index with the probability distribution of the topological charge.

"... In PAGE 13: ...Table1 the distribution for the topological charge using improved cooling 18 is listed along with the distribution for the index obtained using the overlap 19. The two colums are a result of measurements on a di erent set of independent con gurations.... ..."

### Table 9 Relationship of the probability distribution

"... In PAGE 23: ... The second element describes the meaning associated with the second vector in each pair. The third element describes the mathematical relationship of the probability distribution, which is contained in the second data vector to the scale as, for exam- ple, in Table9 , which is the data-base recording of the belief that a user can expect to achieve a continuous session length of between six and seven hours only 45 out of every 100 at- tempts. The levels of service reflected by the reliability measures usually do not have a linear distribution.... ..."

### Table 4.2 Probability Distributions Probability Distribution Extended Form

### Table 2: Sensitization Probability Distribution

2003

"... In PAGE 5: ... It is evident from the results that the proposed scheme reduces the area overhead while providing high coverage in all the cases. In Table2 , we divide the interval [0, 1] into 8 equal subintervals and present the distribution of the num- ber of faults with a sensitization probability over these subintervals. In the table, an entry of x ! y under the interval [0:125; 0:25] indicates that the number of faults with a sensitization probability (= SPparity) in that interval went from x in the unprotected circuit to y (= SP ) in the circuit protected using the proposed scheme.... ..."

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### Table 1: Joint Probability Distribution

"... In PAGE 4: ... Probabilistic/Statistical Reasoning: Many forms of information are inherently probabilistic | eg, given certain symptoms, we may be 80% con dent the patient has hepatitis, or given some evidence, we may be 10% sure a speci c stock will go up in price. One possible downside of dealing with probabilities is the amount of information that has to be encoded: in general one may have to express the entire joint distribution, which is exponential in the number of features; see Table1 . For many years, this observation motivated researchers to seek ways to avoid dealing with probabilities.... In PAGE 4: ... To make this concrete, consider the claims that Hepatitis \causes quot; Jaundice and also \causes quot; a Bloodtest to be positive, in that the chance of these symptoms will increase if the patient has hepatitis. We can represent this information using the full joint over these three binary variables (see Table1 for realistic, if fabricated, numbers), then use this information to compute, for example, P( H j :B ) | the posterior probability that a patient has hepatitis, given that he has a negative blood test. The associated computation, P( H j :B ) = P( H; :B ) P( :B ) = PX62fH;Bg Px2X P( H; :B; X = x ) PX62fBg Px2X P( :B; X = x ) involves the standard steps of marginalization (the summations shown above) to deal with unspec- i ed values of various symptoms, and conditionalization (the division) to compute the conditional probability; see [Fel66].... In PAGE 5: ... While the saving here is relatively small (2 links rather than 3, and a total of 5 parameters, rather than 7), the savings can be very signi cant for larger networks. As a real-world example, the complete joint distribution for the Alarm belief net [BSCC89], which has 37 nodes and 47 arcs, would require approximately 1017 parameters in the naive tabular representation | a la Table1 . The actual belief net, however, only includes 752 parameters.... In PAGE 6: ... There are many obvious connections between the logic-based and probability-based formalisms. For example, we can view the possible worlds (as shown in Table 2) as a \qualitative quot; version of the atomic events (see Table1 ), with the understanding that each \impossible quot; world has probability 0 of occuring, and the other possible words have non-0 probability. Many, including Nilsson [Nil86], have provided formalisms that attempt link these areas.... ..."

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