2. Jim and Catherine are again interested in adjusting the 0-1 variables from Case 2.2 so that theycan examine different scenarios. However, theyrealize that the number of combinations of thetwo 0-1 variables they have control of, low-endversus high-end and mildly aggressive marketing versus very aggressive, is a small number,2×2 = 4. Therefore, they want you to use aRISKSIMTABLE function, with an index from 1to 4, so that a single @RISK run with 4 simulations can be made. You will have to use lookupfunctions so that the two 0-1 variables changeappropriately as the index of RISKSIMTABLEvaries from 1 to 4. As for the third 0-1 variable, whether the competition will introducea competing product, they want you to modelthis probabilistically, using a RISKBERNOULLIfunction with parameter 0.3. This simply indicates that there is a 30% chance of a competingproduct
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
2. Jim and Catherine are again interested in adjusting the 0-1 variables from Case 2.2 so that they
can examine different scenarios. However, they
realize that the number of combinations of the
two 0-1 variables they have control of, low-end
versus high-end and mildly aggressive marketing versus very aggressive, is a small number,
2×2 = 4. Therefore, they want you to use a
RISKSIMTABLE function, with an index from 1to 4, so that a single @RISK run with 4 simulations can be made. You will have to use lookup
appropriately as the index of RISKSIMTABLE
varies from 1 to 4. As for the third 0-1 variable, whether the competition will introduce
a competing product, they want you to model
this probabilistically, using a RISKBERNOULLI
function with parameter 0.3. This simply indicates that there is a 30% chance of a competing
product
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