Question 13.
In a traditionally drawn decision tree, a circle represents ___________.
A. a chance to which no expected monetary value can be assigned so that a likely pay-off can not be shown.
B. a decision to which no expected monetary value can be assigned so that a likely pay-off can not be shown.
C. a chance to which an expected monetary value may be assigned to calculate the most likely pay-off.
D. a decision to which an expected monetary value may be assigned to calculate the most likely pay-off.
Oliver 75 - 13th Question
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Oliver 75 - 13th Question
Jyoti Gupta
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iZenbridge Consultancy Pvt Ltd
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- jyotimayank
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Re: Oliver 75 - 13th Question
In a traditionally drawn decision tree, a circle represents ___________.
Yes the correct answer is option D : a decision to which an expected monetary value may be assigned to calculate the most likely pay-off.
A decision tree is one of the tools used to determine quantitative risk analysis used to reach a computed optimal solution using probability distributions as a basis. The circle represents a "chance node," meaning a chance to which an Expected Monetary Value (EMV) may be assigned to calculate the most likely pay-off.
For more details on this topic please refer to the following link
http://www.izenbridge.com/videogallery/ ... 11-part-6/
Jyoti Gupta
PMP Mentor & Coach
iZenbridge Consultancy Pvt Ltd
PMP Mentor & Coach
iZenbridge Consultancy Pvt Ltd
Re: Oliver 75 - 13th Question
I guess the answer is C. A circle is a chance node.
Some facts on decision trees.
Tree is build left to right but evaluated right to left. This process is known as rolling back the tree.
There two nodes
Chance node: we can calculate the expected payoff represented by the probability distribution at the node.
Decision node: we calculate the largest expected payoff to determine the best action.
Some facts on decision trees.
Tree is build left to right but evaluated right to left. This process is known as rolling back the tree.
There two nodes
Chance node: we can calculate the expected payoff represented by the probability distribution at the node.
Decision node: we calculate the largest expected payoff to determine the best action.
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