Materials for Lecture 08. Chapters 4 and 5 Chapter 16 Sections 3.23.7.3 Lecture 08 Bernoulli . xlsx Lecture 08 Normality Test.xls Lecture 08 Simulation Model with Simetar.xlsx Lecture 08 Normal.xls Lecture 08 Simulate a Reg Model.xls. Stochastic Simulation.
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Iterations, How Many are Enough?
Specify the number of iterations in the Simetar simulation engine
Specify the output variables’ names and location
Probability Density Function
Cumulative Distribution Function
f(x)
F(x)

+

+
=NORM( Mean, Standard Deviation)
=NORM( 10,3)
=NORM( A1, A2)
=NORM(0,1) or =NORM()
Ỹ = Mean + Standard Deviation * NORM(0,1)
Ỹ = Mean + Standard Deviation * SND
Ỹ = A1 + (A2 * A3) where a SND is in cell A3
=TNORM( Mean, Std Dev, [Min], [Max],[USD] )
=TNORM( 10, 3, 5)
=TNORM( 10, 3, , 15)
=TNORM( 10, 3, 5, 15)
=TNORM( 10, 3, 5, 15, [USD])
The values in [ ] are optional
Example Model of Net Returns for a Business Model
 Stochastic Variables  Yield and Price
 Management Variables  Acreage and Costs (fixed and variable)
 KOV  Net Returns
 Write out the equations and exogenous values
Equations and their order
Program a Simulation Model in Excel/Simetar  Input Data Section of the Worksheet
Program Model in Excel/Simetar  Generate Random Variables and Simulate Profit
CDF for Bernoulli B(0.75)
1
.25
.25
.75
0
0
1
X
1
X
PDF and CDF for a Bernoulli Distribution.
Bernoulli Distribution