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!" #
$ $
$ $ % &# ! " # $
& $ ' # % &
' $ # ' ( ) % *
+ *(, + ! + !
& ! - ( !(+! (! +. !
+ ( +& , '-! /! + ! ! +(
0 -' 1!1
+ *( ,( 2334
!,/ -
&-5 ,( ( + / ! + ( ,( 0
! $ $ ( ') !
!" # #
6 7
+
# , ,
!
8
8
( ) 9
" :
& , ;
( < %
( < ,
# " ! #
" ! $7
" - "
": 6
" ,
, 7
": %
; -
8 ( )
; * ;
+ ; : !
,
" : ,
( =#
/ : ! $7
( ; 8 ) = =
1
= : ; = 7 = > = ) =
# ? 7 > = 7
+ ! ; 1
+ *(, + ! + !
& ! - ( !(+! (! +. !
+ ( +& , '-! /! + ! ! +(
0 -' 1!1
+ *( ,( 2334
1. TABLA DE CONTENIDO
@1 - ( ! +-(+ 4
21 +-, !! + A
B1 ,( (+ C
41 -, !- C
D1 "(-* E
D1@1 "(-* 0(+(, E
D121 "(-* ( %(!&! E
F1 " -&! !.+ @3
A1 ! +!( ( % 9 (-( @3
C1 ! +!(%- ' ! @@
C1@1G9 # H @@
C121G9 # H @@
C1B1G9 # 7 ! H @2
C141G9 # 7 H @2
C1D1 ; 7 ! ; H @B
C1F1G!7 7 H @B
C1A1G9 # ; H @4
C1A1@1 0 ; @4
C1A121 ; = 7 @4
C1A1B1 0 @D
C1C1G! ;
! 2333H @D
C1E1G9 # = 7 H @D
C1@31 G9 = 7 = H @F
E1 *(, +( @F
@31 ,(9 (, (+- ( , 5 ,( @C
@@1 ,(9 (, (+- ( &-5 ,( @C
@21 ! ,!,/ - @C
@21@1 G9 I !( !,/ - H @C
@2121 G!7 ; = H @E
@21B1 G!7 ! 8 (6 H 23
@2141 G9 # = H 2B
@2141@1 G!7 = H 2B
@21D1 G!7 = 7 H 2A
@21F1 G!7 7 H 2C
@21A1 G! 8 =
= 7 H B@
@21C1 G!7 ; H BB
@21E1 G!7 = H B4
@21@31 BF
@21@31@1 ; & BF
@21@3121 ! = BA
@21@31B1 % ! BA
@21@3141 !: BC
@21@31D1 - !: BE
@21@31F1 ! - BE
@21@31A1 (6 = BE
@21@@1 ("( % ( % ! !.+ ( ( 43
@21@@1@1 %, (,("( % 1 J& = K 43
@21@@121 (0 + ("( % 1 J* , :K 44
@B1 !,/ - - FC
@B1@1 8 FE
@B1@1@1 : & FE
@B1@121 7 FE
@B1@1B1 - !: FE
@B121 A3
@B121@1 = A3
@B12121 ( 7 A3
@B121B1 A3
@B12141 7 A3
@41 +' ( (,, (+- A@
@41@1 8 L = - M A@
@41@1@1 : & A@
@41@121 7 AD
@41@1B1 ! - !: AE
@4121 C4
@4121@1 = C4
@412121 ( # 7 CD
@41B1 (8 = CF
@41B1@1 - ; = E3
@41B121 ED
@41B1B1 7 ; @33
@D1 0, &N /5( 0, &N @3A
2. INTRODUCCION
! = )
)
> :
) = =
7 ) ; > )
= = ; ; #6 > ;
= = 1
( = ) : ) :
> = !
( 7 ) = )
1
% 7 = (6 O>
= 8 7 >
P ! > : ;
= 7
& ! ( 7 > ) =
= : 6 7 = 7 >
= 7 7 ) )
= = 1
3. RESUMEN
# = :
7 ) ; : ; 7
Q = : # ) :
= = = 7 = =
7 1
(6 : : =
= > 7 = !
= : : > = 7
= ;
Q) =
: ; = ) =
= 1
% > : 7 >
= ; : 8
; > = = ; 7
8 ; Q
7 > > >
4. ABSTRACT
-: : : : : = = P : :
: : : : : : P Q
= : : ) : : = :
= R = = :
1
(6 : ; :
: > P: : ! ; =
: > P : :
< Q :
: P < : == ;
: == = < 1
5 : : : = ; S= S
P: P : : ;
: < > :
= P : P: : :
; = 1
5. OBJETIVOS
5.1. OBJETIVO GENERAL
! 8 : ) P !
O > ) = =
) = ; ! ( 7
; ) = =
= 7 ! ; &!(1
5.2. OBJETIVOS ESPECIFICOS
• ! 8 : ! ) =
; 7 =
) ) 1
• $ = 7 ; ;
P ! 1
• ! ) = : ! O
7 = ; = ! ( 7 1
6. JUSTIFICACIÓN
= 7 = = = =
= = ; 7
1 = = 7
; P Q ;
=T; = 7 # = =
! 1
! P ) = 7
= = 7 = >
=
= > : = 7 1
( = = 7 > )
= 6 >
7 Q
; 1
% # > ! $ = 7
) 7 8
8 7 = > = 7 : ;
= = 7 1
7. ALCANCE DEL PAQUETE
( = = = 7 >
= = ) : ) = =
= 7 > = ; ) = =
7 1
( = ; ) = )
: ; > ) = 7
= ) # = ) ;
= = > = 8
= ; ; ; 1
! = 7 = 7 > = =
=
1 + = )
= ; > = = =
= 7 T 1
8. CONCEPTOS BÁSICOS
8.1. ¿Qué es riesgo?
! 7 = 6= ; >
) = =# #6 > =
; 7 1
= ) =
) ; 1
> = ; )
= = ; > =
= >
) = 1
8.2. ¿Qué es un modelo?
= = ; > 7
> = 7 )
: 8 = = ! 1
% = = ; =
>
= ) #>
; 1
! ) = ;
= > 7 = >
= )
= 7 ; = )
8 7= = = 7 > ;
7 = 7 1
Ilustración 1. Ejemplo de Cristal Ball en MS Excel
! : 7
; : = =
= ) = =
= > ) ) ; ; >
: = > 6 1
8.3. ¿Qué es la simulación Monte Carlo?
7 ) # ;8
= = 7
1 ( = =
= 1
8.4. ¿Qué sucede durante una simulación?
7 T =
= 8 = ;
= ; ; = ;
1 ! 2333 =
L M ) 1
> ! 2333
= ; L ; 7 M
= ; = # : 8 ; 81
; = ; = 1
( = ; 7 ; )
; 1 = ; 7
8.5. De donde obtiene la Simulación Monte Carlo su
nombre?
7 ! ; ! > 7 >
= = 8 Q
> > ) 1
( = 7
! ; > =
1 % 8 = > ; )
T ; @> 2> B> 4> D F = ; =
= 1 (
= = =
L=1 1 = #> = > >
7 = > 1M
8.6. ¿Cómo analizar los resultados de una simulación?
% : 8
= > ; > > )
1 ! 2333 =
= 7 @1 = = 7
> ! = 7
= 1
7 = ; : >
@ = 7 7 )
1
= ; ; > = = 7 1
7 > = = 7
; : ; 7 1 = #
= ;
) 1
Ilustración 2. Cuadro de diálogo - Define Forecast
8.7. ¿Qué es la certeza o certidumbre?
! ; = 8 )
= 7 = 1 %
> =
= > ;# = ; = ; ;
1 ( ! 6 =
= 1 (
8.7.1. Grafica de sensibilidad:
% ; 7 = L ; M
= 7 > ) = 1 %
= = G9 # ;
H ( ; =
; 1
8.7.2. La gráfica de sobreposición:
( = T = = 8> )
# : 8 1 (
8 1 ( : = ;
G! = ; L
MH1
8.7.3. Gráfica de tendencia:
% = 7 ) = 6
; 1 G!7 ;
= H
8.8. ¿Cuales son los beneficios de realizar un análisis de
riesgos con Crystal Ball 2000?
! 8 ! : ; >
=
) = = = 1
! = >
= = 7 : 1
+ 6 : 8 (6
7 ! = T =
: 8 ; >
: ! 1
! ; ! )
1
! ! 7
= > ) : )
= 1
8.9. ¿Qué es Optimización?
= 7 = ) 8 7=
7 = 1 + : 8
= 7 Q ; # =
; ) =
L%1(81 0 M ) 6 )
= ; 1
% 8 = > = 7 = =
; ; 7 = = ;
; ; 1
! : 8 > =
= = = (6 1
; = =
1 ! = 9 > = ! > =
=
: ; = (6 > = ; 8
; 1 > = 9 =
; 7= ;
; = 1
8.10. ¿Que son los pronósticos de series de tiempo?
= 7 = # = 7 )
8 : 7 = = 1 (
: 7 J = K1
9. VERSIONES
( = ) 7 = !
= > ) =
= 5 ;2> = = ; !
! 1
!
• ( 7 ! L ! M
• ( 7 % ! L ! > !
% = 9 M
• ( 7 % ! L ! > ! %
= 9 > ! - ; M
• ( 7 # + =
P = # = = =
$ = 1 ( =
> = =
) =
2 : = ??PPP1 1
: ; : 8
!
( 7 # !
• * 7 ( 7 ;# J 7
6 K> = ) ;
1 ( 7 : ; @43 = #
7 1
• * 7 # ( 7 # =
: ; $ = #
: = 1 % ) 7 ;
= 1
- ;# 7 = ; = ; 5 ;1
7 7 > ) : ; = A
= # 7 1 %
= 5 ; 7 ; 7
= = : > ;
$ 1
% = P >
> = U: P )
; $ 1
= ) = =
) = > ) ; $ 1
: = = =
=
• ! % = = 7 = L
% % =
= 1M
• = 9 > = ; 7 L
% % M
• ! - ; > = = = ; ) =
L 7 % M
• ! - > = 8 7
!
• ! L 7 M
7 = : 1= >
7 = 7 = 1
10. REQUERIMIENTOS DE HARDWARE
• % % ) 433 M
• F4 ,
• B3 = ;
• ! U, L( 7 ! ! M
• - 8 C336F33 = 6
7
11. REQUERIMIENTOS DE SOFTWARE
% 8 ! > ;
P ) = 1
• = 5 P EC> 5 P
( L M> 5 P +-413 5 < % <F
= > 5 P 2333 % > 5 P V% ( >
5 P V%%
• (6 EA> 2333> 2332 LV%M> 233B1
• (6= D13 = 1 L M
• ; ; , 413 = L = =
7 = = M
12. COMO USAR CRYSTAL BALL
12.1. ¿QUÉ HACE CRYSTAL BALL?
! 6 = = ; : 8
(6 = 7 = )
P = 8
1 ! (6 >
• = ; = 1 ! >
6= >
= ) : = ;
1
• ( J5: U K = =
7 ) = ; ; T
= 1
! =
• % ; = ; =
; : 8 1 > )
= ) 6=
= 1
• = ' &!" $ &> !
8 = 7 )
= ; = ; ;
) 1
8 = ; 8 ; 8 =
! 1
12.2. ¿Cómo abrir el programa?
! P =
> : = > ; 8 ;
: 8 = (6 O1 ( =
; ; (6 ! >
; 8 1
% = ! :
; = 8 7 > ; 8 ; 8 =
! %: 1 % ; 8 =
! > = : T 1 T
= ; = 7 !
: ; = 1
= # ; = 7 > ! =
; ; 7 ! ; ; Q
; > = ; ; : = 7 =
(6 L= ) :
7 P M1
Ilustración 3 Barra de tareas ejecutando Crystal Ball
; ! T
+ ! 1
Ilustración 4 Ubicación de Crystal Ball en el menú Inicio
! %: 16 > )
8 = ! 1 ( ; 7 =
; = =
# 1
% = ; ) >
: ) = 7 L M ; ; 81
) L M> ! =
> 8 1
12.3. ¿Cómo Crystal Ball mejora Excel?
: 8 (6 6 : =
> = = 7 : 1
7 (6 ) > =
= Q ) = ;
; 1
! 8 (6 = ;
= >
; 1 % ! T
; : (6 1
Ilustración 5 Barra de Herramientas de CB
! = ; ; : = =
= ) : 1 =
; = 8 6
= ! 1 7
T ; ; = Q
1
T !( L M> ("(! - , L M
! (,, (+- L M1
Ilustración 6 Barra de Menús de Excel con CB
( T!( L M= ! 1
Ilustración 7 Menú Cell
( T ("(! - , L M> =
1
Ilustración 8 Menú Run
( T ! (,, (+- L M
: 7 > : = =
( 7 % ! 1
Ilustración 9 Menú CBTools
12.4. ¿Qué es un supuesto?
( ) : 8 6
; ) = 1 ; (6
= > =
= ; 1
( > ! ;
= ; ; J = K) = = ; ;
= ; = ; 1 ( ;
= ; ; = 7 = ;
; 1 ! ; 7
= = = 1
( 8 = = L! %: M> ; 8
; > L ;#
! = 0 M1
( 7 = =
; 1
12.4.1. ¿Cómo definir un supuesto?
( = = = =
; > > ; ) ;
1
% 8 = ! %: > = 8
; = ) = ;
1
Ilustración 10 Hoja de Calculo del ejemplo CellPhone
% = = ; 7 > L @@M
: ; ; 7 J = KL = M 1
; 7 1 =
! > ) ;
= ) L! @@M1
Ilustración 11 Cuadro de dialogo Distribution Gallery
Ilustración 12 Distribución Triangular para la celda B11
1 = )
; T ) = ; 8 = =
1
= = > > 6 >
= ; ; 1 ( = ;
) T >
8 = ! %: 1 U = : ;
1 % = : ; 7 J = K
L = M1
Ilustración 13 Celda supuesto % Long Distance (B11)
;
L @3M1 : ; ; 7
J = KL = M1 : ; 7
1
; ) = = : ; 43 >
) = B43 4F31 =
7 > ; 7 231
Ilustración 14 Distribución Normal para la celda B10
: ; = L M 1 ( !
= = ) 1
Ilustración 15 Celda supuesto Actual Minutes (B10)
( = = 7 !
1
12.5. ¿Cómo definir un pronóstico?
: ; ! 1 (
= 7 > ) 7 )
= U = 1 = 7 ;
#> ) Q 0 + > *
= + > ! = % , 1
= = 7 ) 1 ! !
7 >
= 7 1 = =
) 8 1
( ) = ; 7 &E>
= = > = #
; > = : ; (6 1
L! M =
= 7 L @4M1 : ; ; 7
J % 7 KL & M 1
% L! @4 & M ;
= =
= LWM
Ilustración 16 Cuadro de dialogo Define Forecast
! : L! M : ;
> ) ) = 7 = ! 1
Ilustración 17 Celda pronostico B14
: = 7 1
12.6. ¿Cómo correr una simulación?
! 7 ! B
=
: 8
1 ( ) J5: U K
= > = ; 1
% = > ;) ;
U= 7 : ; 7 J% % K
L =M ; 1
= = L =M !
= = 1 :
BE3 ! " BBX1
3
http://www.decisioneering.com/models/beginner.html
Ilustración 18 Nuevos valores para el modelo al correr la simulación
(6 : 8
= 7 W21DB1 ( ! :
W41F@1
: ; 7 J% = KL =M ;
: 8 =
= 7 ; 1
= ; ) U= 7
= = = # 1
% ; 7 L
X M> ) 433 B3X = =
> : ; 7 J, K ; 1
% = > ) 8 = >
7 J(8 7 K L,
% M = 8 7
> ) ; T )
1
Ilustración 19 Cuadro de dialogo Run Preferences
#( T 6 @3333
: ; 7 J(8 K L, M
L ;
= = =
(8 7 M1
; = 7 Y:
= U 1
Ilustración 20 Gráfica de pronósticos para la celda Cost Savings (B14)
12.7. ¿Como analizar los resultados arrojados por el cuadro
de pronósticos?
7 = = 7
8 > = 1
#% ; =
1
( = 7 = ) =
; = = =
> = = ;
; = = 7 1
; T*(, = 7 L M
= ; 8 = 7
) >
6 ) ; = =
= # > = ! %: 1
Ilustración 21 Cuadro de estadísticas para la celda B14
( = 7 = ; :
= 8 1 % 8 =
= ; ) C3X :
W@1A31
Ilustración 22 Cuadro de Percentiles para la celda B14
( : ) W41F@ ) : ; = :
; ) = ;
: = 1
: = = ; 7 ! 8 ;
! ; L !: M1
12.8. ¿Cómo usar el cuadro de sensibilidad?
= ; = ; =
; > = )
= 1
% 6 = ; = 7 =
: # $ ! 1 %
> : ; 7 J! ; KL
!: M 1
Ilustración 23 Cuadro de Sensibilidad medida por el rango de correlación
=
= 7 1 : ; ; 7 %&
L! % M> =
% L% ; M> : ; = 7 $
' > ; ) = L
M ; A41B X ! : 1
Ilustración 24 Cuadro de Sensibilidad medida por la Contribución a ala varianza
; )
7 > ) ) ) :
: ; > : ) 1 % !
" 7 = > ) = 8
> 8
(
+ ! = T
= > ;
: T ) = = 1
8 ) = ) :
= > = ; =
= 1 % = 8 = > ; )
7 =
> = =
= Q > 1
12.9. ¿Cómo generar un reporte?
% = 7 ! 1
% : ; ; 7 J! = KL! , = M
: ! 1
Ilustración 25 – Cuadro de diálogo Create Report
=
) ) ) = = ) $ LZM>
= = ; LZM>
7 ; = LZM>
; = 7 (6 LZMQ
? = ; ; 8 ; )
; 8 LZM1
( = ) ! > 7 )
: L 7 2DM1
8 7 ; T = = >
= 8 = $ > =
= ) : : : ;
) 8 1
#( ; = ;
7 1 ! : = )
6= > = =
= 1
12.10. Otros recursos
12.10.1. Distribution Fitting
: 7 ) = = >
= = 7 ; & = ; ; 7 J& K
J ; 0 K1
Ilustración 26 Galería de Distribuciones
Ilustración 27 Cuadro de dialogo Fit Distribution
12.10.2. Correlated Assumptions
: ; = > 7 >
7 ) =
7 1 ( : : :
: 8 ; 8 (6 1
( ; 7 % ) = )
= 1
Ilustración 28 Cuadro de dialogo Correlación
12.10.3. Precision Control
( ! % 7 ! = )
) T 8
= = = 1 ( = 7 ; 7
% ! 1
Ilustración 29 Cuadro PrecisionControl
12.10.4. Overlay Chart
) = = 7 > J : K
= T = = 7 ; 7
1 ( : = ; ; T (
Ilustración 30 Cuadro de dialogo Overlay Chart
12.10.5. Trend Chart
* + T = = 7 > =
; ; = ;
1 ( : = ; ;
T (
Ilustración 31 Cuadro de Tendencias
12.10.6. CB Tools
= = = ) 8 7
! = : 1
12.10.7. Example Models
! : 8 = ) =
; 8 = = : = 7
= # T 1
12.11. EJEMPLOS DE APLICACIÓN DE MODELOS
12.11.1. PRIMER EJEMPLO. “Futura Apartments”
( 8 = > = = 8
& = 1 7 ) = 7
B3 ; ; 8 =
7 1
Ilustración 32 Hoja de Calculo “Futura Apartments”
! ; 8 : =
• WD33 = =
• ( T )
B3 43
• = 7 = W@D1333
= = = 8 > = =
= > ) ; ) ;
= 8 = ;
= 7 1 ( = : : 8
: ; L ! M> ) =
= = )
(6 1
> ; : 8
: ; : = ; 8 #
J5: U J> ) =
1 / ) ;
)
7 1 ! ! ; 1
Correr la simulación
% 7 ; =
• ,
• 8 7 ! 7
= 7 6= 8 = * +
* " ! + = # : ;
8 6 = LD33 = M>
; 1
( = 7 = # T 6
> = 1
Ilustración 33 Pronósticos de Ganancia/Perdida para FA
• =
• % 8 7 = 7 > ;
: > , [ =1
+ 1 = 7 =
(6 7 > = >
= [- ;1
( = 7 = =#
= : = 7 & = 1 ! ;
= = ; = ; ;
1 ( =
= ; ; > = W2D3
W4AD3 = 1 ! ;# = = > )
= = W2333 8
) WA3331
Determinar el beneficio
: = ! = = ; ;
; >
= ; ; 1 % = ; ; > ;
= ; ; = 7 8
• % $ = )
) = 7
• ( ; 3 L M =
• %
Ilustración 34 Probabilidad de Ganancia para FA
( = ; L! M ; = 8
= ; ; = W3 =
: = > ) : : 1 !
7 > 8 = 7 =
7 & = 1 -
7 B> =
; L0 W3M = 6 EBX1
+ ;# ) = W2333>
; > : 1
Como usa Crystal Ball la simulación de Montecarlo
( = ; ; )
: = 8 ) 1 (6
: ; = = ;
1 7 # )
) T ; T
T = 1
( = ) T :
)
• 7 6
• ( 7
( = 7 8 ; ;
U = ; 1 , ) 7
! = = 6 7 1
! = = : 8
> ; 6 = ;
= : )
= 6 = ; 1
! ;# = ) ;
= 7 8 1
% = 8 =
• , [ ,
• = =
; 1
•
• 7 ; = 7
= 1
• ! : 8 8 =
12.11.2. SEGUNDO EJEMPLO. “Vision Research”
( 8 = 7 : ) =
6 : !
: = = 1
( 8 = ) * , :4
7
; 1 = * , : :
= > ! U
* P> ) = 1 ( = =
= = ; = > =
= 76 $ & = ; = 1 )
; 8 ; = = > #6
) & = ; = 1
* , : = ! )
; =
> = ; 1 ( = ! * P
= 1 ! =
= = 7 > $ =
1
% ; ; 8 ! 7 =
• ; : 8 ' =
8 = ! > T ! [ % [
! [ (6 =
: 8 = * , : = = !
* P = > 7 2B1
4
http://www.crystalball.com/models/pharma.html
Ilustración 35 Hoja de calculo ejemplo Vision Research
( : 8 = ; ) * , :
1
Definir supuestos
( ! > = = = U
; 7 = ; ; ) ;
; ) 1 % >
; : @A = ; 7 )
0 ; > 0 ;
; : ! >
; = 7 = L 7 DM1
G!7 ; ) = ; 7 H1 ( =
= = ; 7 ;
= ) = ; 1 ( 8 = >
U = : 8 * , :
8 ; = ; ; ) 6 ;
; = ! * P1
( 8 = > 6= = ; 7
= = = 1
Definir Testing Costs. La Distribución Uniforme
: > * , : : W@313331333
! * P = WB13331333 W
D13331333 = = ; > ; = ;
1 % ; > J- K> * , : )
) WB13331333 W D13331333
= ; ; 1
! > * , : 7 ; 7
= ; J- ! K = ; 1 ; 7
; 7
6 6 = ; ;
) > ; 7 ) 8 ;
8 = 7 = $ = ! % ;
= 1
= ; 7 > =
U = 1 % = = -
!
• !D
• ( T > : ; = 7
= : ; :
! 1 ( J $ ) , -+ =
Ilustración 36 Cuadro de dialogo “Distribution Gallery”
• ; ; 7 ( '
• ,
( J ; 7 K =
Ilustración 37 Cuadro de dialogo “Distribución Uniforme”
) !D ; ; : 8
> ; = = J = + K
; = 1 ; = ; >
; 1 > ) ! =
; 7 1
; 7 = >
6 1 * , : = = ;
WB13331333 6 WD133313331
) = = = = =
; 7 ! >
• ( ; B = L ) T : 8
= 7 M1
( = WB13331333> ) *
, : = = ; L- ! M1
• % + 8 =
• ( ; D =
( = WD13331333> 6 =
= ; L- ! M1
•
; 7 ; = 8 ; ) : : :
> 7 2F
Ilustración 38 Distribución Uniforme para la celda C5
= >
; 7 ; = 7 2F1
> = = 1 = #>
7 > ! = !D )
B D 7 1
• ! = : 8
Definir Costos de marketing: La Distribución Triangular
* , : = ; <
! * P> = ; = & 1 ( =
= =
= $ = ; = =T;
= 1
= ; > * , : = W@213331333
W@C13331333> W@F13331333 = ; ; 1
* , : 7 ; 7 = ;
! < > ) ; 7 ; 7
= 6 > = ; ;
1
% U = = ! < L <
! M
• !F
• ; = 7
= : ; : ! 1 (
J $ ) , -+ = 1
• ; J ; 7 - K
•
( J ; 7 - K =
Ilustración 39 Cuadro de dialogo “Distribución Triangular”
: = ) = = ; 7 1 !
= ; 7 2A> = =
; 7 = =
; 7 1
• ( ; @2 =
( = W@213331333> ) *
, : = ! <
• % = = ". / # $ $ 0(
@F> ; 1
( = W@F13331333> = ; ; =
! <
• % ; @C =
( = W@C13331333> 6 =
! <
•
; 7 ; = 8 1
Ilustración 40 Distribución Triangular para la celda C6
7 > ! )
@F @2 @C1
• = : 8
Definir pacientes curados: La Distribución Binomial
) & = ; ! * P> * , : ;
= ; ; @33 =
$ 1 * , : = ) & = ; =
! * P = = 23 = >
) ) T 1 ( = ; > 23X
= ; 7
= # ! * P = $ 1 * , :
> = # = ; = )
= 8 #6 2DX1
% ; > J= K> * , :
= ; = > ) #6 2DX1
G* , : = = & H1 !
> * , : 7 ; 7 ; = ;
; ) = 7 Q ) ; 7
; ; T 6 L2DM T
= L@33M1
% U = = J% K> =
• !@3
• ; = 7 ( '*
; =
• ; 7
•
• ( * $ ) + = 1 L&8
) = = = = ; ; 31D
D3XM1
•
Ilustración 41 Cuadro de dialogo “Distribución Binomial”
• ; 7 ; = % ; ;
L $1M L 0( ; ) * , :
= 8 6 2DX = ; = )
> 312D = =
= ; ; = = ; )
6 1
• 1 = 6= = ; ;
3 @> 313B> T
= 8> BX1
•
• ; ) & = ) * , :
= ; @33 = > @33 = 6=
; 7 ; 1 %
=
•
• ( ; 312D =
• ( = 2DX = ; ;
=
• = @33> = $
• ( ; @33 =
• ( = @33 = )
= & 1
• :
• ; 7 ; = 8
•
Ilustración 42 Distribución Binomial para la celda C10
7 > ! T 3
@33> = ) =
& 1
• = : 8
Tasa de crecimiento: La Distribución Personalizada
* , : : ) = = 6
4313331333 = ( = 8
3X DX = 7
$ ) ! * P = ; 1
; > = < : )
6 = ; 2DX ) = =
= 1 ( = =
! * P DX @DX1
( ; J- = K = =
; 7 = ; ; 1 % )
; ) T > *
, : ; 7 = ! =
1 % > ; 7
= = ; ) =
; 7 = 1
( # = = = ; 7
= = ; >
; = 1
> : 0 = ; >
= = = B1
; 7 = =
7 = ! * P1 % U
= = =
• !@D
• ; = 7
• ; 7 L% M
•
( ; 7 % = 1 +7
) 7 B@ ) =
; > ) 8
8 1
Ilustración 43 Cuadro de dialogo “Distribución Personalizada”
% =
• ( ; 3X =
( = 3X =
• %
• ( ; DX =
( = DX =
• %
• ( ; ADX =
( = = ; ; ) = *
, : = 7 = = 7
* , :1
•
; 7 3X DX = 1
Ilustración 44 Distribución Personalizada para C15
%
• ( ; U@DX =
( = @DX 7 =
• %
• ( ; UDX =
( = DX 7 =
• %
• ( ; 2DX =
( = 2DX = ; ) = *
, : = 7 = = 7
DX @DX
•
; 7 = @DX UDX = 1
; = : *
$ +1
Ilustración 453 Distribución personalizada para C15 (2 Supuesto)
% ; 7 = T
= : 8 ;
= 1 (
7 ! )
= = 1
• = : 8
Definir penetración en el mercado: La distribución normal
( = < ) = 7
= = 7 = * , :
; CX
7 2X1 J+ ; K )
* , : = ; =
FCX = ; = = 7
7 = ; 8
7 = >
FX @3X1
( > CX> )
>
= ; = 1 = <
DX> = #
= = 1
* , : 7 ; 7 = ; ;
J < % K1 % U = =
= 7
• !@E
• = 7
• ; 7 +
•
( J+ ; K =
Ilustración 34 Cuadro de dialogo “Distribución Normal”
: = ) = = ; 7
7
• = C133X> ; CX
= ( = = CX =
= 7 1
• %
• ( ; 2X = !
( = 2X = 7 1
•
• ; 7 = 8 >
) ; 7 ; > ;
= = ; 1
• %
• ( ; DX = = ) = 7
=
• ( = DX ) =
= 1
•
• ; 7 ; = 8 1
Ilustración 35 Distribución Normal para la celda C19
7 > ! )
; 7 ) CX
= ; 8 DX ) 1
= : 8 1
Definir pronósticos
= # U = > =
U= 7 1 ( )
U = 1
= * , : = ; ;
; = > = ; ;
; > = 1 (
= 7 = ; L!2@M ;
L!2BM= = ! * P1
Calcular el beneficio total
! = = 7
7 1 ( > = = ;
; U= 1 %
= ; 1
• !2@
( = ; =
= : 8 1 !@F!@E!231 !
= ; =
= = = # $ L!@FM =
= 7 L!@EM ; = L!23M1
= # = ;
> = U= = ;
1 %
• ( T : ; = 7 "
( J % + = 1 ( =
; = = 7 1 ; > )
= 7 ; : 8 >
; = = 1 % ;
; ; 1
Ilustración 36 “Definir Pronostico” para C21
• %
• ( ; J K = # > =
) 8
• = : 8
Calcular el beneficio neto
U= = ; >
; = ;
• !2B
• ( = ; = =
: 8 1 ( ] L!@@Q!2@U!AQU!4U!DM
& = ; L!@@ * M>
; L!AM ;
L!2@M1 ; > & = ; L!@@
& M> ; +
L!4M ! ( L!DM) : : 1
% U= = ;
• ( T : ; = 7 "
Ilustración 46 “Definir Pronostico “ para C23
+ ; = ) = =
= ) 7 = #
1
• %
• ( ; J K = #
• = : 8
> : = = 7 =
* , :> ; : 8 )
; = Q
7 1
Correr la simulación
! 7 ! >
; 7 ) 1
1 = T -% 8 = >
7 =
= = T1 7 >
1
= 7 > = ) T
> ) 7 8
= 7 1
% = T
• = 7 $% & [ ' T
• ( J, % - K = 1
• ( = .' ' '/ ( & L 6 M>
; D33
• (L M
• = 7 J ' 0 ! ( $ '
'/ 1L T M
• ( = ) ; EEE
•
Ver los cuadros de pronósticos
; ) = 7 =
; = 1 ; > 6
= 7 1 (
: = 7
; 1
= ( ( ** $
( ; L0 % M = >
7 BC
Ilustración 47 Cuadro de Pronostico para “Net Profit”
= 7 2" * + ,& T
" = %
> 1
7 > ; 7
= = 7 = = 8 ;
U= 1 ; 7 =
;
; 7 T
= 1 ( 7 BC>
; 7 = 7
+ @F = = )
1 ( ) @F
= 1
, ) = 7
= ; 1 =
) 7 = > ! T
; 7 = U= )
8 6 1
Interpretar los resultados
Entender el cuadro de pronóstico
! = = =
* , :1 ; > = 7
T 6= > ) =
8 ) 6 6 = 1
( 7 BC>
W@41A : WB414> = 7
+ 1
( = 7 ;# ; =
= 7 1 % > ;
: = 1
! = T ;
T > =
; 1 ( 8 = : ;
@33X> ) ;
= ; 1 , ) ; = 6 7 >
) : 8 = = 6
1
( ) = ) > ! T
) 8 = = 7 1 ( =
= : > = 1
; ) 6 = > T
6 = )
7 1
Determinar el nivel de certidumbre
: = * , : ) ; )
= ; = ;
= 1 % ;
=
• ( = 7 + % > = - ;
• ( ; 3 =
• % (
! ; ; =
) > = = W313
; 1
= J+ % K> = ; )
;
; AE1C3X1 ( ) * , :
AE1C3X = ; ; 1
= = ) 6 = ; 2312X
= L@33X AE1C3XM1
: = * , : ) ;
; W2133313331 ! !
= = = 1
Ilustración 48 Pronostico para “Net Profit” con valores positivos
• ( ; 2 =
• %
! 7 BE> !
; W213 ; 1
Ilustración 49 Pronostico para “Net Profit”
* , : = ; AB1F3X =
; W2133313331
* , : ; =
= 7 1 : = ; )
= ; ; W4133313331
! ) * , : =
; W413331333 ; > =
= = = 7 = 1
> ! = = = 1
• ( ; 4 =
• %
! ; W413
;
Ilustración 50Pronostico para “Net Profit” (2)
( = 7 J- & 7 4@
; FFX1 ! ; =
; W4133313331 * , : ;
= ! * P =
= 1
13. CRYSTAL BALL TOOLS
: ! = * )
= 1 % 7
:
= = 7 >
7 > ) = 7
; )
= 1
( : ) ! = 7
D
: &
! 7
( - !:
=
- ; =
(
7
7 ;
> 8>
= ; > 8
5
http://www.crystalball.com/crystal_ball/cbtools.html
13.1. Herramientas de Montaje del modelo
7
13.1.1. Batch Fit
: & : = ;
= F
1
! (6 ; :
! > T! - = = >
: & 1
13.1.2. Matriz de correlación
( : ) = 6
= = Q : =
) ; 8 = > >
;
7 > = :
= ) 6
1 = > = 8 = 1
13.1.3. Tornado Chart
( = = ) ;
; ;8 > 8 6
; > = = 1
6
http://www.crystalball.com/spotlight/spotlight10.html
13.2. Herramientas de análisis
13.2.1. Bootstrap
( # = = 7 ? ;
= = = 7
= 1 > : )
; >
= = = 7 >
7 > 1
13.2.2. Escenario de decisión
( = =
6 ; 7 = >
7 Q
7 1
13.2.3. Análisis de escenarios
) = ; =
> ) = ; =
= ) = = 1
( = 7
= > = = 7 >
7 > = > 1
13.2.4. Simulación Bidimensional:
= ; )
= = 7 >
7 =
1
( ; ) ; =
= 7 >
7 ; = L )
= $ ; 6= M>
) L: M>
7 ; 67 >
= >
; T
=
; L 7
T = M
14. ANÁLISIS DE LAS HERRAMIENTAS
: = = ; =
8 = )
1 7 8 = =
: L 8 M> =
= ; =
7 1
14.1. Herramientas de Montaje (Setup Tools)
% : 8 =
; * *
! 7 ; 1
14.1.1. Batch Fit o Herramientas de serie
Ilustración 51 Asistente de Batch Fit
( # = ; = ; ; T =
> = ; = ; ;
L > > > 1M= ) T
= = 7 ) ; 1
# = : =
7 > 7 = >
; 7 = ; ; ; = )
8 1
( : = > =
> = ; ; 8 > !: U > Q
7 = = ; = ; 7 )
8 = = 7 7
1
( : = : )
= = ; > =
= ; ) 8 Q
> = (6 > = >
8 ) 1
Ejemplo
( = ; = 8
; ! ; >
Q= 8 ; ;
= > = = @EEC 233B> =
= : ;
= 7 ; 1
% 8 : &
( = = ; : (6 >
; ! > T ! - : 1
= : & > = @ B
; 1
( = 2 B = >
=
= =
1
> = 7
> = ; : 8 1
! ; =
: 1
= 7 7 >
; 7 = ; ; = 1
% B B
)
= 1
( = = ; 7 7
> ) = 3 @1
= = 7 ; 7
> = = = 1
: > = : 8
! = = = T 7
(6 > ; = = ; :
= 1
( T , = 7 = ; =
7 T
7 ! > =
^ = 7 ,
: & 8 = > = =
>
= = 1 % :
= 1
Ilustración 52. Vista “Statistics”. Observese que el coeficiente de variación es del 9%.
: 7 =
= > 8 ! % >
= = = 7 8 = 7 1
! : J : & K 8 >
= ; 7 > 8 ; 7
= $ > )
1
( ) = )
= 7 L& M= WD1233> =
; 7 = E@>2X = 6
= ; = : ; 1
Ilustración 53 . “Frequency chart” del ejemplo
14.1.2. Matriz de correlación
Ilustración 54 Matriz de Correlación
) 6 ;
= = > =
= 7 U= >
= 7 = 7
; =
= 6
= 7 1 = ; ; =
) 6 >
A
(6 7
7 =
( 7 $ ) ;
7
Cárdenas Héctor, Curso de Econometría, capitulo 2. Profesor de la Facultad de Ciencias Económicas de la
Universidad Nacional de Colombia
= L ; 6=
6= M> = 7 = 7
= Q= 8 =
=
/] @2>B2@4CEEC _ 3>3EACDFCB V@ _ 3>42F4442@ V2_ 3>4DBF4CFA VB
- ; 67 6=
V@ = 7
V2 6= 7 = 7
VB 6= 7 Q
; ) : ; 6= ) ;
= ; 7 6= > >
/ = 7 = 7 ! ;
7
7 6 ; ) ; 6=
= > ) ; 7
Q = =
) ; > = ; ;
) = = 1
7 C
= 6 ) ;
= 6= = 7 > 6
7 = > )
: @ = 6 ;
8 7 6 1
8
Mide el grado de asociación lineal entre la variable dependiente (endógena) y la independiente o exógena,
eliminando el efecto de las demás variables del modelo
! = T = ; =
= 7 6 )
; > = 7 ; =
> > = > 1
( = 7 ; : =
T ! - > = 7
= = > =
7
= = 1 > = =
: 8
> ; = : = )
7 1
7 = =
= >
$ 7 ; > =
: 1
Ilustración 55 – Matriz de correlación
7 > ! ;
8 > = ) 1
Ejemplo
! 8 = * ;
> = ; 7 =
L > = 7 7 M ;
6= > Q
7 = = 1
7 T
= 8 1
% 8 ! 7 >
; ! (6 ; :
! = 8 LK KM>
8 = > > =
= 7 L D33M>
LEEEM ! 1
, 7 = 7 J K
7 L M1
= 7 = ;
7 DF1
Ilustración 56 Cuadro de EStadisticas
! - > 7
= 7 Q
; ;# = = = :
; ; = 8 =
1
( $ >
= > = 8 7 1 (
7
2333
233@
2332
233B
! 7
2333 @>333 3>233 3>B33 3>@33
! 7
233@ @>333 3>@33 3>B33
! 7
2332 @>333 3>433
! 7
233B @>333
( ; ) 8 ; ) >
= ) ) =
J K = = >
7 8 1
> 7
! 1
7 = 7
> ) =
1
14.1.3. Cuadro Tornado Chart
Ilustración 57 Asistente de Tornado Chart
( : = ;
> # 7 > )
: = ; = > 7 = ) ; >
; > = = Q
; > ; = 1
= ) ; ;
= 7 Q ) ; >
: # ;# ; J= ; 7
= K J = # K1
( - : = = ; 7
`- !:
` = !:
) = ! ) 2D3 ;
= : = : 1
Tornado Chart
( : = ; ;
= = > = 7
= > $ = 7= 6
= 7 = ; > >
) ; = 7
( : = ; ;
! > ;
8 ; > :
; 7 1
; 7 )
; = 7 Q= ; ) =
= 7 $ ; )
81
(6 = 7 = ;
> 6 7 ;
# = 1 6
= 7 = = ; > ;
7 U
= 7 1
Spider Chart
$ 6 6
= 7 = ) #
; = ; 1 ! =
> = > ) ;
; ; = 7 Q )
: = ) $ ; = 7 1
Ejemplo:
% 8 = ; ;
: 8 ) # > = )
= = 8 1
; T ! - > - !: > =
> ;8 L= @ BM1
!
; L= 2 BM
= 1 !
) ; ) ;
1
! 1
( = B B ; = =
L @3X E3XM
T = L DM> =
6 L 8 =
= 7 M
( = 7 = = 7 ( #
- = = = ; 1
= 7 - !: = !:
! 1
: - !:
= !: >
8 = = : 1
Ilustración 58 - Tornado Chart
Ilustración 59 - Spider Chart
( 8 = > 4 = = >
; >
; > = 7
; ; = ; 81
- !: = !:
; ) :
= ; ; = > =
= = ; =
7 1
8 = : =
6 = = ; ; 8 >
6
@33X > 7 = ;
= ; : = = ;
1 ( = ; ; )
7 7 ; 1
14.2. Herramientas de Análisis
14.2.1. Bootstrap
Ilustración 60 - Asistente para Bootstrap
( # ) ) 6
= 7 Q
: ) ; 7
= 6 > =
1
: # ; > =
) = ; 7 >
= = 7 1
! ) = ; => = 6
> = ;
; > = 7 ;
> = =
# 1
7 ; 7 =
; = ; ;
1
(6 # =
( # = ; = # 7 T
( >
= ; ) #
7 > 1 7
; = 1
( ) = # = ; =
7 6
= 7 ; 7 ; = >
; Q # 7
= ) > ) = 8 7 7
: ) # 7 1
14.2.2. El método de la Multisimulación
! = >
; 7 > = =
7 = =
7 = > ; 7 7
L M1 % = 7
= = = 7 = ; =
7 1
( # 7 ) = ;
= # > = # : > = ;
5 6 > U5: > Q =
= ; 7 ) = :
Q ; = =
; 7 1
( ; = = ; >
= 6 = >
# = 8 > ) ;
T = = ; =
= = 1
Ilustración 61 – Comparación única simulación vs. Multisimulación Fuente: Tools tutorial
14.3. Ejemplo:
% = 8 = > )
= = ; > 7 ; 1
( ) : ; )
= : ! Q =
; (6 ; : = 8 = = >
= : ) = ; ! =
8 ) = 7 1
Ilustración 62 – Vision general Modelo “Planta energia nuclear”
! - > = 7 =
; = ;8 )
1
6 =#
= = 7 > 7
= = 2 B ; )
# T 7 = ; = #
) = # 1 ! 1
( = = B B = )
= T > = =
D33 > $ 7 = 7 1 ! 1
T, = >
= 1
= = 6
@X EEX> = 1
% 7 ; =
= > > 7 > >
> < 7 Q
= = =
6 > : 1
= ; = = = 7
= = ) = ) >
) ; = 1
Ilustración 63 – Frecuency chart para la variable “Mean”
! 7 L M
7 > = ;
; = ) ) 1
( 6 7 )
Q = ;
7 >
7 > ; 7
; 7 1
% = 8 > 6=
; = > $ 7
7
(
*
<P
^
!
7
, 3>C2 3>C2 3>32 3>33 3>33 B>3A 3>32
!
@>333
3>AC3 U
3>3EA
U
3>3EA 3>3@4
U
3>@FB
U
3>@2B
@>333 U
3>3EC
U
3>3EC
U
3>2EB
U
3>3FA
U
3>@@E
7
( @>333 @>333
U
3>@CF 3>@A2 3>EEE
*
@>333
U
3>@CF 3>@A2 3>EEE
< P
@>333
U
3>BFD
U
3>@CF
^
@>333 3>@AD
!
* 7 @>333
Ilustración 64
14.3.1. Tabla para la toma de decisiones
Ilustración 65 - Asistente para la Tabla de decisiones
; 7 ) = >
) ; = = >
8 ; = = 1 + ;
; > = ; )
; 7 ; = 7 1
( : ; = 7 ;
7 ; 7
= 7 1
% ) ; 7 >
) = = 7
> 8; = 9 ! 1
+ ; = 9 >
) : Q = ; J = 9 K
= J K) ; !
: 7= = 7 >
; 1 E
Ejemplo
! 8 ! 7 ; > )
; 8 = 7 = )
; = ; >
7 = ; 7 >
= ; =
8 = 1
% ; : ; ! >
TJ K = T
7 T
> EEE1
• 7 ! > ;
; = = =
: T, 1
• ! ^1
• = 7 ! - > ) = ;
7 > ;8
1
• ( 8 = 7 1
E
! ; ) : :
= ; ! % 233312> 7 = 1
• ! > = 7
=
• ; 7 1 ! 1
) = = = = ;
7 ) 1 ! 1
= )
= > $ ; > T =
7 L= ; ; D33M1 ! 1
L3>BFM
L3>BFCCCCCEM
L3>BAAAAAACM
L3>BCFFFFFAM
L3>BEDDDDDFM
L3>43444444M
L3>4@BBBBBBM
L3>42222222M
L3>4B@@@@@@M
L3>44M
%
L@BD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE @
%
L@BCBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE 2
%
L@4@FF>FFFFAM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE B
%
L@4D33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE 4
%
L@4CBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE D
%
L@D@FF>FFFFAM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE F
%
L@DD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE A
%
L@DCBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE C
% 3>C@ 3>C2 3>CB 3>C4 3>C4 3>CD 3>CF 3>CA 3>CC 3>CE E
L@F@FF>FFFFAM
%
L@FD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE @3
@ 2 B 4 D F A C E @3
: 8 7 = ; 7 )
; 7 > = ;
= = 7 1
% > = =
;# 7 > )
7 7 = Q
; 6 : T = 8
7 ; ; 7 >
: = > 1
% 7 = T = 7
; > $ > ) 6=
# > )
L > > 1M
= = 7 7=
J ; 7 K> > ) = ;
> 7 )
= = > ) 8
= ; 1
=
= ) $
! = ; 7
= ; U
= $
=
=
= ; 7
*1 1
= ; 7
>
! = 7
=
*
=
= 7
=
G
;
; H >
G
>
7
(6
; >
= 7 ; >
; >
= a G 8
=
6=
= ;
G(
H
>
; 7 >
= >
= > = ; = ; 7
; 7 742 > = ; 7
) = ; >
) 7 8 8 = 8
= > 8 ; 7 ; @D31
% = ; 7 >
7 J, K 8 >
; % 7 1 ( ) =
= ; > :
1
14.3.2. Análisis de escenario
Ilustración 66 - Asistente para el análisis de escenario
( = = =
7 > ) !
= 7 ; = 7 >
= = > = = L@XM
) = = EE =
; 8 L@X1M
%
= 7 > ) = > ) = : ) #
= ; 1
Ejemplo
J= K>
; : = = =
> ; 8 = = > =
; > = = Q :
= )
= 8 7 = > =
= =
= ) 1
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Hoffman, F. O. and J. S. Hammonds. “Propagación de la incertidumbre en situaciones de riesgo: La
necesidad de distinguir entre incertidumbre debida a la falta de conocimiento y la incertidumbre ocasionada
por la variabilidad” Análisis de Riesgo, vol. 14, no. 5. pp 707-712, 1994.
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Crystal ball

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  • 2. !,/ - &-5 ,( ( + / ! + ( ,( 0 ! $ $ ( ') ! !" # # 6 7 + # , , ! 8 8 ( ) 9 " : & , ; ( < % ( < , # " ! # " ! $7 " - " ": 6 " , , 7 ": % ; - 8 ( ) ; * ; + ; : ! , " : , ( =# / : ! $7 ( ; 8 ) = = 1 = : ; = 7 = > = ) = # ? 7 > = 7 + ! ; 1
  • 3. + *(, + ! + ! & ! - ( !(+! (! +. ! + ( +& , '-! /! + ! ! +( 0 -' 1!1 + *( ,( 2334
  • 4. 1. TABLA DE CONTENIDO @1 - ( ! +-(+ 4 21 +-, !! + A B1 ,( (+ C 41 -, !- C D1 "(-* E D1@1 "(-* 0(+(, E D121 "(-* ( %(!&! E F1 " -&! !.+ @3 A1 ! +!( ( % 9 (-( @3 C1 ! +!(%- ' ! @@ C1@1G9 # H @@ C121G9 # H @@ C1B1G9 # 7 ! H @2 C141G9 # 7 H @2 C1D1 ; 7 ! ; H @B C1F1G!7 7 H @B C1A1G9 # ; H @4 C1A1@1 0 ; @4 C1A121 ; = 7 @4 C1A1B1 0 @D C1C1G! ; ! 2333H @D C1E1G9 # = 7 H @D C1@31 G9 = 7 = H @F E1 *(, +( @F
  • 5. @31 ,(9 (, (+- ( , 5 ,( @C @@1 ,(9 (, (+- ( &-5 ,( @C @21 ! ,!,/ - @C @21@1 G9 I !( !,/ - H @C @2121 G!7 ; = H @E @21B1 G!7 ! 8 (6 H 23 @2141 G9 # = H 2B @2141@1 G!7 = H 2B @21D1 G!7 = 7 H 2A @21F1 G!7 7 H 2C @21A1 G! 8 = = 7 H B@ @21C1 G!7 ; H BB @21E1 G!7 = H B4 @21@31 BF @21@31@1 ; & BF @21@3121 ! = BA @21@31B1 % ! BA @21@3141 !: BC @21@31D1 - !: BE @21@31F1 ! - BE @21@31A1 (6 = BE @21@@1 ("( % ( % ! !.+ ( ( 43 @21@@1@1 %, (,("( % 1 J& = K 43 @21@@121 (0 + ("( % 1 J* , :K 44 @B1 !,/ - - FC @B1@1 8 FE
  • 6. @B1@1@1 : & FE @B1@121 7 FE @B1@1B1 - !: FE @B121 A3 @B121@1 = A3 @B12121 ( 7 A3 @B121B1 A3 @B12141 7 A3 @41 +' ( (,, (+- A@ @41@1 8 L = - M A@ @41@1@1 : & A@ @41@121 7 AD @41@1B1 ! - !: AE @4121 C4 @4121@1 = C4 @412121 ( # 7 CD @41B1 (8 = CF @41B1@1 - ; = E3 @41B121 ED @41B1B1 7 ; @33 @D1 0, &N /5( 0, &N @3A
  • 7. 2. INTRODUCCION ! = ) ) > : ) = = 7 ) ; > ) = = ; ; #6 > ; = = 1 ( = ) : ) : > = ! ( 7 ) = ) 1 % 7 = (6 O> = 8 7 > P ! > : ; = 7 & ! ( 7 > ) = = : 6 7 = 7 > = 7 7 ) ) = = 1
  • 8. 3. RESUMEN # = : 7 ) ; : ; 7 Q = : # ) : = = = 7 = = 7 1 (6 : : = = > 7 = ! = : : > = 7 = ; Q) = : ; = ) = = 1 % > : 7 > = ; : 8 ; > = = ; 7 8 ; Q 7 > > > 4. ABSTRACT -: : : : : = = P : : : : : : : : P Q = : : ) : : = : = R = = : 1 (6 : ; : : > P: : ! ; = : > P : : < Q : : P < : == ; : == = < 1 5 : : : = ; S= S P: P : : ; : < > : = P : P: : : ; = 1
  • 9. 5. OBJETIVOS 5.1. OBJETIVO GENERAL ! 8 : ) P ! O > ) = = ) = ; ! ( 7 ; ) = = = 7 ! ; &!(1 5.2. OBJETIVOS ESPECIFICOS • ! 8 : ! ) = ; 7 = ) ) 1 • $ = 7 ; ; P ! 1 • ! ) = : ! O 7 = ; = ! ( 7 1
  • 10. 6. JUSTIFICACIÓN = 7 = = = = = = ; 7 1 = = 7 ; P Q ; =T; = 7 # = = ! 1 ! P ) = 7 = = 7 = > = = > : = 7 1 ( = = 7 > ) = 6 > 7 Q ; 1 % # > ! $ = 7 ) 7 8 8 7 = > = 7 : ; = = 7 1 7. ALCANCE DEL PAQUETE ( = = = 7 > = = ) : ) = = = 7 > = ; ) = = 7 1 ( = ; ) = ) : ; > ) = 7 = ) # = ) ; = = > = 8 = ; ; ; 1 ! = 7 = 7 > = = = 1 + = ) = ; > = = = = 7 T 1
  • 11. 8. CONCEPTOS BÁSICOS 8.1. ¿Qué es riesgo? ! 7 = 6= ; > ) = =# #6 > = ; 7 1 = ) = ) ; 1 > = ; ) = = ; > = = > ) = 1 8.2. ¿Qué es un modelo? = = ; > 7 > = 7 ) : 8 = = ! 1 % = = ; = > = ) #> ; 1 ! ) = ; = > 7 = > = ) = 7 ; = ) 8 7= = = 7 > ; 7 = 7 1
  • 12. Ilustración 1. Ejemplo de Cristal Ball en MS Excel ! : 7 ; : = = = ) = = = > ) ) ; ; > : = > 6 1 8.3. ¿Qué es la simulación Monte Carlo? 7 ) # ;8 = = 7 1 ( = = = 1 8.4. ¿Qué sucede durante una simulación? 7 T = = 8 = ; = ; ; = ; 1 ! 2333 = L M ) 1 > ! 2333 = ; L ; 7 M = ; = # : 8 ; 81 ; = ; = 1 ( = ; 7 ; ) ; 1 = ; 7
  • 13. 8.5. De donde obtiene la Simulación Monte Carlo su nombre? 7 ! ; ! > 7 > = = 8 Q > > ) 1 ( = 7 ! ; > = 1 % 8 = > ; ) T ; @> 2> B> 4> D F = ; = = 1 ( = = = L=1 1 = #> = > > 7 = > 1M 8.6. ¿Cómo analizar los resultados de una simulación? % : 8 = > ; > > ) 1 ! 2333 = = 7 @1 = = 7 > ! = 7 = 1 7 = ; : > @ = 7 7 ) 1
  • 14. = ; ; > = = 7 1 7 > = = 7 ; : ; 7 1 = # = ; ) 1 Ilustración 2. Cuadro de diálogo - Define Forecast 8.7. ¿Qué es la certeza o certidumbre? ! ; = 8 ) = 7 = 1 % > = = > ;# = ; = ; ; 1 ( ! 6 = = 1 ( 8.7.1. Grafica de sensibilidad: % ; 7 = L ; M = 7 > ) = 1 % = = G9 # ; H ( ; = ; 1 8.7.2. La gráfica de sobreposición: ( = T = = 8> ) # : 8 1 ( 8 1 ( : = ; G! = ; L MH1
  • 15. 8.7.3. Gráfica de tendencia: % = 7 ) = 6 ; 1 G!7 ; = H 8.8. ¿Cuales son los beneficios de realizar un análisis de riesgos con Crystal Ball 2000? ! 8 ! : ; > = ) = = = 1 ! = > = = 7 : 1 + 6 : 8 (6 7 ! = T = : 8 ; > : ! 1 ! ; ! ) 1 ! ! 7 = > ) : ) = 1 8.9. ¿Qué es Optimización? = 7 = ) 8 7= 7 = 1 + : 8 = 7 Q ; # = ; ) = L%1(81 0 M ) 6 ) = ; 1 % 8 = > = 7 = = ; ; 7 = = ; ; ; 1 ! : 8 > = = = = (6 1 ; = = 1 ! = 9 > = ! > = = : ; = (6 > = ; 8
  • 16. ; 1 > = 9 = ; 7= ; ; = 1 8.10. ¿Que son los pronósticos de series de tiempo? = 7 = # = 7 ) 8 : 7 = = 1 ( : 7 J = K1 9. VERSIONES ( = ) 7 = ! = > ) = = 5 ;2> = = ; ! ! 1 ! • ( 7 ! L ! M • ( 7 % ! L ! > ! % = 9 M • ( 7 % ! L ! > ! % = 9 > ! - ; M • ( 7 # + = P = # = = = $ = 1 ( = > = = ) = 2 : = ??PPP1 1
  • 17. : ; : 8 ! ( 7 # ! • * 7 ( 7 ;# J 7 6 K> = ) ; 1 ( 7 : ; @43 = # 7 1 • * 7 # ( 7 # = : ; $ = # : = 1 % ) 7 ; = 1 - ;# 7 = ; = ; 5 ;1 7 7 > ) : ; = A = # 7 1 % = 5 ; 7 ; 7 = = : > ; $ 1 % = P > > = U: P ) ; $ 1 = ) = = ) = > ) ; $ 1 : = = = = • ! % = = 7 = L % % = = 1M • = 9 > = ; 7 L % % M • ! - ; > = = = ; ) = L 7 % M • ! - > = 8 7 ! • ! L 7 M 7 = : 1= > 7 = 7 = 1
  • 18. 10. REQUERIMIENTOS DE HARDWARE • % % ) 433 M • F4 , • B3 = ; • ! U, L( 7 ! ! M • - 8 C336F33 = 6 7 11. REQUERIMIENTOS DE SOFTWARE % 8 ! > ; P ) = 1 • = 5 P EC> 5 P ( L M> 5 P +-413 5 < % <F = > 5 P 2333 % > 5 P V% ( > 5 P V%% • (6 EA> 2333> 2332 LV%M> 233B1 • (6= D13 = 1 L M • ; ; , 413 = L = = 7 = = M 12. COMO USAR CRYSTAL BALL 12.1. ¿QUÉ HACE CRYSTAL BALL? ! 6 = = ; : 8 (6 = 7 = ) P = 8 1 ! (6 > • = ; = 1 ! > 6= > = ) : = ; 1 • ( J5: U K = =
  • 19. 7 ) = ; ; T = 1 ! = • % ; = ; = ; : 8 1 > ) = ) 6= = 1 • = ' &!" $ &> ! 8 = 7 ) = ; = ; ; ) 1 8 = ; 8 ; 8 = ! 1 12.2. ¿Cómo abrir el programa? ! P = > : = > ; 8 ; : 8 = (6 O1 ( = ; ; (6 ! > ; 8 1 % = ! : ; = 8 7 > ; 8 ; 8 = ! %: 1 % ; 8 = ! > = : T 1 T = ; = 7 ! : ; = 1 = # ; = 7 > ! = ; ; 7 ! ; ; Q ; > = ; ; : = 7 = (6 L= ) : 7 P M1 Ilustración 3 Barra de tareas ejecutando Crystal Ball ; ! T + ! 1
  • 20. Ilustración 4 Ubicación de Crystal Ball en el menú Inicio ! %: 16 > ) 8 = ! 1 ( ; 7 = ; = = # 1 % = ; ) > : ) = 7 L M ; ; 81 ) L M> ! = > 8 1 12.3. ¿Cómo Crystal Ball mejora Excel? : 8 (6 6 : = > = = 7 : 1 7 (6 ) > = = Q ) = ; ; 1 ! 8 (6 = ;
  • 21. = > ; 1 % ! T ; : (6 1 Ilustración 5 Barra de Herramientas de CB ! = ; ; : = = = ) : 1 = ; = 8 6 = ! 1 7 T ; ; = Q 1 T !( L M> ("(! - , L M ! (,, (+- L M1 Ilustración 6 Barra de Menús de Excel con CB ( T!( L M= ! 1 Ilustración 7 Menú Cell ( T ("(! - , L M> = 1
  • 22. Ilustración 8 Menú Run ( T ! (,, (+- L M : 7 > : = = ( 7 % ! 1 Ilustración 9 Menú CBTools
  • 23. 12.4. ¿Qué es un supuesto? ( ) : 8 6 ; ) = 1 ; (6 = > = = ; 1 ( > ! ; = ; ; J = K) = = ; ; = ; = ; 1 ( ; = ; ; = 7 = ; ; 1 ! ; 7 = = = 1 ( 8 = = L! %: M> ; 8 ; > L ;# ! = 0 M1 ( 7 = = ; 1 12.4.1. ¿Cómo definir un supuesto? ( = = = = ; > > ; ) ; 1 % 8 = ! %: > = 8 ; = ) = ; 1
  • 24. Ilustración 10 Hoja de Calculo del ejemplo CellPhone % = = ; 7 > L @@M : ; ; 7 J = KL = M 1 ; 7 1 = ! > ) ; = ) L! @@M1
  • 25. Ilustración 11 Cuadro de dialogo Distribution Gallery Ilustración 12 Distribución Triangular para la celda B11 1 = ) ; T ) = ; 8 = = 1
  • 26. = = > > 6 > = ; ; 1 ( = ; ) T > 8 = ! %: 1 U = : ; 1 % = : ; 7 J = K L = M1 Ilustración 13 Celda supuesto % Long Distance (B11) ; L @3M1 : ; ; 7 J = KL = M1 : ; 7 1 ; ) = = : ; 43 > ) = B43 4F31 = 7 > ; 7 231 Ilustración 14 Distribución Normal para la celda B10 : ; = L M 1 ( ! = = ) 1
  • 27. Ilustración 15 Celda supuesto Actual Minutes (B10) ( = = 7 ! 1 12.5. ¿Cómo definir un pronóstico? : ; ! 1 ( = 7 > ) 7 ) = U = 1 = 7 ; #> ) Q 0 + > * = + > ! = % , 1 = = 7 ) 1 ! ! 7 > = 7 1 = = ) 8 1 ( ) = ; 7 &E> = = > = # ; > = : ; (6 1 L! M = = 7 L @4M1 : ; ; 7 J % 7 KL & M 1 % L! @4 & M ; = = = LWM Ilustración 16 Cuadro de dialogo Define Forecast ! : L! M : ;
  • 28. > ) ) = 7 = ! 1 Ilustración 17 Celda pronostico B14 : = 7 1 12.6. ¿Cómo correr una simulación? ! 7 ! B = : 8 1 ( ) J5: U K = > = ; 1 % = > ;) ; U= 7 : ; 7 J% % K L =M ; 1 = = L =M ! = = 1 : BE3 ! " BBX1 3 http://www.decisioneering.com/models/beginner.html
  • 29. Ilustración 18 Nuevos valores para el modelo al correr la simulación (6 : 8 = 7 W21DB1 ( ! : W41F@1 : ; 7 J% = KL =M ; : 8 = = 7 ; 1 = ; ) U= 7 = = = # 1 % ; 7 L X M> ) 433 B3X = = > : ; 7 J, K ; 1 % = > ) 8 = > 7 J(8 7 K L, % M = 8 7 > ) ; T ) 1
  • 30. Ilustración 19 Cuadro de dialogo Run Preferences #( T 6 @3333 : ; 7 J(8 K L, M L ; = = = (8 7 M1 ; = 7 Y: = U 1
  • 31. Ilustración 20 Gráfica de pronósticos para la celda Cost Savings (B14) 12.7. ¿Como analizar los resultados arrojados por el cuadro de pronósticos? 7 = = 7 8 > = 1 #% ; = 1 ( = 7 = ) = ; = = = > = = ; ; = = 7 1 ; T*(, = 7 L M = ; 8 = 7 ) > 6 ) ; = = = # > = ! %: 1
  • 32. Ilustración 21 Cuadro de estadísticas para la celda B14 ( = 7 = ; : = 8 1 % 8 = = ; ) C3X : W@1A31 Ilustración 22 Cuadro de Percentiles para la celda B14 ( : ) W41F@ ) : ; = : ; ) = ; : = 1 : = = ; 7 ! 8 ; ! ; L !: M1
  • 33. 12.8. ¿Cómo usar el cuadro de sensibilidad? = ; = ; = ; > = ) = 1 % 6 = ; = 7 = : # $ ! 1 % > : ; 7 J! ; KL !: M 1 Ilustración 23 Cuadro de Sensibilidad medida por el rango de correlación = = 7 1 : ; ; 7 %& L! % M> = % L% ; M> : ; = 7 $ ' > ; ) = L M ; A41B X ! : 1
  • 34. Ilustración 24 Cuadro de Sensibilidad medida por la Contribución a ala varianza ; ) 7 > ) ) ) : : ; > : ) 1 % ! " 7 = > ) = 8 > 8 ( + ! = T = > ; : T ) = = 1 8 ) = ) : = > = ; = = 1 % = 8 = > ; ) 7 = > = = = Q > 1 12.9. ¿Cómo generar un reporte? % = 7 ! 1 % : ; ; 7 J! = KL! , = M : ! 1
  • 35. Ilustración 25 – Cuadro de diálogo Create Report = ) ) ) = = ) $ LZM> = = ; LZM> 7 ; = LZM> ; = 7 (6 LZMQ ? = ; ; 8 ; ) ; 8 LZM1 ( = ) ! > 7 ) : L 7 2DM1 8 7 ; T = = > = 8 = $ > = = ) : : : ; ) 8 1 #( ; = ; 7 1 ! : = ) 6= > = = = 1
  • 36. 12.10. Otros recursos 12.10.1. Distribution Fitting : 7 ) = = > = = 7 ; & = ; ; 7 J& K J ; 0 K1 Ilustración 26 Galería de Distribuciones Ilustración 27 Cuadro de dialogo Fit Distribution
  • 37. 12.10.2. Correlated Assumptions : ; = > 7 > 7 ) = 7 1 ( : : : : 8 ; 8 (6 1 ( ; 7 % ) = ) = 1 Ilustración 28 Cuadro de dialogo Correlación 12.10.3. Precision Control ( ! % 7 ! = ) ) T 8 = = = 1 ( = 7 ; 7 % ! 1
  • 38. Ilustración 29 Cuadro PrecisionControl 12.10.4. Overlay Chart ) = = 7 > J : K = T = = 7 ; 7 1 ( : = ; ; T ( Ilustración 30 Cuadro de dialogo Overlay Chart
  • 39. 12.10.5. Trend Chart * + T = = 7 > = ; ; = ; 1 ( : = ; ; T ( Ilustración 31 Cuadro de Tendencias 12.10.6. CB Tools = = = ) 8 7 ! = : 1 12.10.7. Example Models ! : 8 = ) = ; 8 = = : = 7 = # T 1
  • 40. 12.11. EJEMPLOS DE APLICACIÓN DE MODELOS 12.11.1. PRIMER EJEMPLO. “Futura Apartments” ( 8 = > = = 8 & = 1 7 ) = 7 B3 ; ; 8 = 7 1 Ilustración 32 Hoja de Calculo “Futura Apartments” ! ; 8 : = • WD33 = = • ( T ) B3 43 • = 7 = W@D1333 = = = 8 > = = = > ) ; ) ; = 8 = ; = 7 1 ( = : : 8 : ; L ! M> ) = = = ) (6 1 > ; : 8 : ; : = ; 8 # J5: U J> ) =
  • 41. 1 / ) ; ) 7 1 ! ! ; 1 Correr la simulación % 7 ; = • , • 8 7 ! 7 = 7 6= 8 = * + * " ! + = # : ; 8 6 = LD33 = M> ; 1 ( = 7 = # T 6 > = 1 Ilustración 33 Pronósticos de Ganancia/Perdida para FA • = • % 8 7 = 7 > ; : > , [ =1 + 1 = 7 = (6 7 > = > = [- ;1
  • 42. ( = 7 = =# = : = 7 & = 1 ! ; = = ; = ; ; 1 ( = = ; ; > = W2D3 W4AD3 = 1 ! ;# = = > ) = = W2333 8 ) WA3331 Determinar el beneficio : = ! = = ; ; ; > = ; ; 1 % = ; ; > ; = ; ; = 7 8 • % $ = ) ) = 7 • ( ; 3 L M = • % Ilustración 34 Probabilidad de Ganancia para FA ( = ; L! M ; = 8 = ; ; = W3 = : = > ) : : 1 ! 7 > 8 = 7 =
  • 43. 7 & = 1 - 7 B> = ; L0 W3M = 6 EBX1 + ;# ) = W2333> ; > : 1 Como usa Crystal Ball la simulación de Montecarlo ( = ; ; ) : = 8 ) 1 (6 : ; = = ; 1 7 # ) ) T ; T T = 1 ( = ) T : ) • 7 6 • ( 7 ( = 7 8 ; ; U = ; 1 , ) 7 ! = = 6 7 1 ! = = : 8 > ; 6 = ; = : ) = 6 = ; 1 ! ;# = ) ; = 7 8 1 % = 8 = • , [ , • = = ; 1 • • 7 ; = 7 = 1 • ! : 8 8 =
  • 44. 12.11.2. SEGUNDO EJEMPLO. “Vision Research” ( 8 = 7 : ) = 6 : ! : = = 1 ( 8 = ) * , :4 7 ; 1 = * , : : = > ! U * P> ) = 1 ( = = = = ; = > = = 76 $ & = ; = 1 ) ; 8 ; = = > #6 ) & = ; = 1 * , : = ! ) ; = > = ; 1 ( = ! * P = 1 ! = = = 7 > $ = 1 % ; ; 8 ! 7 = • ; : 8 ' = 8 = ! > T ! [ % [ ! [ (6 = : 8 = * , : = = ! * P = > 7 2B1 4 http://www.crystalball.com/models/pharma.html
  • 45. Ilustración 35 Hoja de calculo ejemplo Vision Research ( : 8 = ; ) * , : 1 Definir supuestos ( ! > = = = U ; 7 = ; ; ) ; ; ) 1 % > ; : @A = ; 7 ) 0 ; > 0 ; ; : ! > ; = 7 = L 7 DM1 G!7 ; ) = ; 7 H1 ( = = = ; 7 ; = ) = ; 1 ( 8 = > U = : 8 * , : 8 ; = ; ; ) 6 ; ; = ! * P1
  • 46. ( 8 = > 6= = ; 7 = = = 1 Definir Testing Costs. La Distribución Uniforme : > * , : : W@313331333 ! * P = WB13331333 W D13331333 = = ; > ; = ; 1 % ; > J- K> * , : ) ) WB13331333 W D13331333 = ; ; 1 ! > * , : 7 ; 7 = ; J- ! K = ; 1 ; 7 ; 7 6 6 = ; ; ) > ; 7 ) 8 ; 8 = 7 = $ = ! % ; = 1 = ; 7 > = U = 1 % = = - ! • !D • ( T > : ; = 7 = : ; : ! 1 ( J $ ) , -+ =
  • 47. Ilustración 36 Cuadro de dialogo “Distribution Gallery” • ; ; 7 ( ' • , ( J ; 7 K = Ilustración 37 Cuadro de dialogo “Distribución Uniforme” ) !D ; ; : 8 > ; = = J = + K ; = 1 ; = ; > ; 1 > ) ! = ; 7 1 ; 7 = > 6 1 * , : = = ; WB13331333 6 WD133313331 ) = = = = = ; 7 ! > • ( ; B = L ) T : 8 = 7 M1 ( = WB13331333> ) * , : = = ; L- ! M1 • % + 8 =
  • 48. • ( ; D = ( = WD13331333> 6 = = ; L- ! M1 • ; 7 ; = 8 ; ) : : : > 7 2F Ilustración 38 Distribución Uniforme para la celda C5 = > ; 7 ; = 7 2F1 > = = 1 = #> 7 > ! = !D ) B D 7 1 • ! = : 8 Definir Costos de marketing: La Distribución Triangular * , : = ; < ! * P> = ; = & 1 ( = = = = $ = ; = =T; = 1 = ; > * , : = W@213331333 W@C13331333> W@F13331333 = ; ; 1
  • 49. * , : 7 ; 7 = ; ! < > ) ; 7 ; 7 = 6 > = ; ; 1 % U = = ! < L < ! M • !F • ; = 7 = : ; : ! 1 ( J $ ) , -+ = 1 • ; J ; 7 - K • ( J ; 7 - K = Ilustración 39 Cuadro de dialogo “Distribución Triangular” : = ) = = ; 7 1 ! = ; 7 2A> = = ; 7 = = ; 7 1
  • 50. • ( ; @2 = ( = W@213331333> ) * , : = ! < • % = = ". / # $ $ 0( @F> ; 1 ( = W@F13331333> = ; ; = ! < • % ; @C = ( = W@C13331333> 6 = ! < • ; 7 ; = 8 1 Ilustración 40 Distribución Triangular para la celda C6 7 > ! ) @F @2 @C1 • = : 8 Definir pacientes curados: La Distribución Binomial
  • 51. ) & = ; ! * P> * , : ; = ; ; @33 = $ 1 * , : = ) & = ; = ! * P = = 23 = > ) ) T 1 ( = ; > 23X = ; 7 = # ! * P = $ 1 * , : > = # = ; = ) = 8 #6 2DX1 % ; > J= K> * , : = ; = > ) #6 2DX1 G* , : = = & H1 ! > * , : 7 ; 7 ; = ; ; ) = 7 Q ) ; 7 ; ; T 6 L2DM T = L@33M1 % U = = J% K> = • !@3 • ; = 7 ( '* ; = • ; 7 • • ( * $ ) + = 1 L&8 ) = = = = ; ; 31D D3XM1 •
  • 52. Ilustración 41 Cuadro de dialogo “Distribución Binomial” • ; 7 ; = % ; ; L $1M L 0( ; ) * , : = 8 6 2DX = ; = ) > 312D = = = ; ; = = ; ) 6 1 • 1 = 6= = ; ; 3 @> 313B> T = 8> BX1 • • ; ) & = ) * , : = ; @33 = > @33 = 6= ; 7 ; 1 % = • • ( ; 312D = • ( = 2DX = ; ; =
  • 53. • = @33> = $ • ( ; @33 = • ( = @33 = ) = & 1 • : • ; 7 ; = 8 • Ilustración 42 Distribución Binomial para la celda C10 7 > ! T 3 @33> = ) = & 1 • = : 8 Tasa de crecimiento: La Distribución Personalizada * , : : ) = = 6 4313331333 = ( = 8 3X DX = 7 $ ) ! * P = ; 1 ; > = < : ) 6 = ; 2DX ) = =
  • 54. = 1 ( = = ! * P DX @DX1 ( ; J- = K = = ; 7 = ; ; 1 % ) ; ) T > * , : ; 7 = ! = 1 % > ; 7 = = ; ) = ; 7 = 1 ( # = = = ; 7 = = ; > ; = 1 > : 0 = ; > = = = B1 ; 7 = = 7 = ! * P1 % U = = = • !@D • ; = 7 • ; 7 L% M • ( ; 7 % = 1 +7 ) 7 B@ ) = ; > ) 8 8 1
  • 55. Ilustración 43 Cuadro de dialogo “Distribución Personalizada” % = • ( ; 3X = ( = 3X = • % • ( ; DX = ( = DX = • % • ( ; ADX = ( = = ; ; ) = * , : = 7 = = 7 * , :1 • ; 7 3X DX = 1
  • 56. Ilustración 44 Distribución Personalizada para C15 % • ( ; U@DX = ( = @DX 7 = • % • ( ; UDX = ( = DX 7 = • % • ( ; 2DX = ( = 2DX = ; ) = * , : = 7 = = 7 DX @DX • ; 7 = @DX UDX = 1 ; = : * $ +1
  • 57. Ilustración 453 Distribución personalizada para C15 (2 Supuesto) % ; 7 = T = : 8 ; = 1 ( 7 ! ) = = 1 • = : 8 Definir penetración en el mercado: La distribución normal ( = < ) = 7 = = 7 = * , : ; CX 7 2X1 J+ ; K ) * , : = ; = FCX = ; = = 7 7 = ; 8 7 = > FX @3X1 ( > CX> ) > = ; = 1 = <
  • 58. DX> = # = = 1 * , : 7 ; 7 = ; ; J < % K1 % U = = = 7 • !@E • = 7 • ; 7 + • ( J+ ; K = Ilustración 34 Cuadro de dialogo “Distribución Normal” : = ) = = ; 7 7 • = C133X> ; CX = ( = = CX = = 7 1 • % • ( ; 2X = !
  • 59. ( = 2X = 7 1 • • ; 7 = 8 > ) ; 7 ; > ; = = ; 1 • % • ( ; DX = = ) = 7 = • ( = DX ) = = 1 • • ; 7 ; = 8 1 Ilustración 35 Distribución Normal para la celda C19 7 > ! ) ; 7 ) CX = ; 8 DX ) 1 = : 8 1 Definir pronósticos
  • 60. = # U = > = U= 7 1 ( ) U = 1 = * , : = ; ; ; = > = ; ; ; > = 1 ( = 7 = ; L!2@M ; L!2BM= = ! * P1 Calcular el beneficio total ! = = 7 7 1 ( > = = ; ; U= 1 % = ; 1 • !2@ ( = ; = = : 8 1 !@F!@E!231 ! = ; = = = = # $ L!@FM = = 7 L!@EM ; = L!23M1 = # = ; > = U= = ; 1 % • ( T : ; = 7 " ( J % + = 1 ( = ; = = 7 1 ; > ) = 7 ; : 8 > ; = = 1 % ; ; ; 1
  • 61. Ilustración 36 “Definir Pronostico” para C21 • % • ( ; J K = # > = ) 8 • = : 8 Calcular el beneficio neto U= = ; > ; = ; • !2B • ( = ; = = : 8 1 ( ] L!@@Q!2@U!AQU!4U!DM & = ; L!@@ * M> ; L!AM ; L!2@M1 ; > & = ; L!@@ & M> ; + L!4M ! ( L!DM) : : 1 % U= = ; • ( T : ; = 7 "
  • 62. Ilustración 46 “Definir Pronostico “ para C23 + ; = ) = = = ) 7 = # 1 • % • ( ; J K = # • = : 8 > : = = 7 = * , :> ; : 8 ) ; = Q 7 1 Correr la simulación ! 7 ! > ; 7 ) 1 1 = T -% 8 = > 7 = = = T1 7 > 1 = 7 > = ) T > ) 7 8 = 7 1 % = T • = 7 $% & [ ' T • ( J, % - K = 1 • ( = .' ' '/ ( & L 6 M> ; D33
  • 63. • (L M • = 7 J ' 0 ! ( $ ' '/ 1L T M • ( = ) ; EEE • Ver los cuadros de pronósticos ; ) = 7 = ; = 1 ; > 6 = 7 1 ( : = 7 ; 1 = ( ( ** $ ( ; L0 % M = > 7 BC Ilustración 47 Cuadro de Pronostico para “Net Profit” = 7 2" * + ,& T " = % > 1 7 > ; 7 = = 7 = = 8 ;
  • 64. U= 1 ; 7 = ; ; 7 T = 1 ( 7 BC> ; 7 = 7 + @F = = ) 1 ( ) @F = 1 , ) = 7 = ; 1 = ) 7 = > ! T ; 7 = U= ) 8 6 1 Interpretar los resultados Entender el cuadro de pronóstico ! = = = * , :1 ; > = 7 T 6= > ) = 8 ) 6 6 = 1 ( 7 BC> W@41A : WB414> = 7 + 1 ( = 7 ;# ; = = 7 1 % > ; : = 1 ! = T ; T > = ; 1 ( 8 = : ; @33X> ) ; = ; 1 , ) ; = 6 7 > ) : 8 = = 6 1 ( ) = ) > ! T ) 8 = = 7 1 ( = = : > = 1 ; ) 6 = > T
  • 65. 6 = ) 7 1 Determinar el nivel de certidumbre : = * , : ) ; ) = ; = ; = 1 % ; = • ( = 7 + % > = - ; • ( ; 3 = • % ( ! ; ; = ) > = = W313 ; 1 = J+ % K> = ; ) ; ; AE1C3X1 ( ) * , : AE1C3X = ; ; 1 = = ) 6 = ; 2312X = L@33X AE1C3XM1 : = * , : ) ; ; W2133313331 ! ! = = = 1
  • 66. Ilustración 48 Pronostico para “Net Profit” con valores positivos • ( ; 2 = • % ! 7 BE> ! ; W213 ; 1 Ilustración 49 Pronostico para “Net Profit” * , : = ; AB1F3X = ; W2133313331 * , : ; = = 7 1 : = ; ) = ; ; W4133313331 ! ) * , : = ; W413331333 ; > = = = = 7 = 1 > ! = = = 1 • ( ; 4 = • % ! ; W413 ;
  • 67. Ilustración 50Pronostico para “Net Profit” (2) ( = 7 J- & 7 4@ ; FFX1 ! ; = ; W4133313331 * , : ; = ! * P = = 1
  • 68. 13. CRYSTAL BALL TOOLS : ! = * ) = 1 % 7 : = = 7 > 7 > ) = 7 ; ) = 1 ( : ) ! = 7 D : & ! 7 ( - !: = - ; = ( 7 7 ; > 8> = ; > 8 5 http://www.crystalball.com/crystal_ball/cbtools.html
  • 69. 13.1. Herramientas de Montaje del modelo 7 13.1.1. Batch Fit : & : = ; = F 1 ! (6 ; : ! > T! - = = > : & 1 13.1.2. Matriz de correlación ( : ) = 6 = = Q : = ) ; 8 = > > ; 7 > = : = ) 6 1 = > = 8 = 1 13.1.3. Tornado Chart ( = = ) ; ; ;8 > 8 6 ; > = = 1 6 http://www.crystalball.com/spotlight/spotlight10.html
  • 70. 13.2. Herramientas de análisis 13.2.1. Bootstrap ( # = = 7 ? ; = = = 7 = 1 > : ) ; > = = = 7 > 7 > 1 13.2.2. Escenario de decisión ( = = 6 ; 7 = > 7 Q 7 1 13.2.3. Análisis de escenarios ) = ; = > ) = ; = = ) = = 1 ( = 7 = > = = 7 > 7 > = > 1 13.2.4. Simulación Bidimensional: = ; ) = = 7 > 7 = 1 ( ; ) ; = = 7 > 7 ; = L ) = $ ; 6= M> ) L: M> 7 ; 67 > = >
  • 71. ; T = ; L 7 T = M 14. ANÁLISIS DE LAS HERRAMIENTAS : = = ; = 8 = ) 1 7 8 = = : L 8 M> = = ; = 7 1 14.1. Herramientas de Montaje (Setup Tools) % : 8 = ; * * ! 7 ; 1 14.1.1. Batch Fit o Herramientas de serie Ilustración 51 Asistente de Batch Fit ( # = ; = ; ; T = > = ; = ; ; L > > > 1M= ) T = = 7 ) ; 1 # = : =
  • 72. 7 > 7 = > ; 7 = ; ; ; = ) 8 1 ( : = > = > = ; ; 8 > !: U > Q 7 = = ; = ; 7 ) 8 = = 7 7 1 ( : = : ) = = ; > = = ; ) 8 Q > = (6 > = > 8 ) 1 Ejemplo ( = ; = 8 ; ! ; > Q= 8 ; ; = > = = @EEC 233B> = = : ; = 7 ; 1 % 8 : & ( = = ; : (6 > ; ! > T ! - : 1 = : & > = @ B ; 1 ( = 2 B = > = = = 1 > = 7 > = ; : 8 1 ! ; = : 1 = 7 7 > ; 7 = ; ; = 1
  • 73. % B B ) = 1 ( = = ; 7 7 > ) = 3 @1 = = 7 ; 7 > = = = 1 : > = : 8 ! = = = T 7 (6 > ; = = ; : = 1 ( T , = 7 = ; = 7 T 7 ! > = ^ = 7 , : & 8 = > = = > = = 1 % : = 1 Ilustración 52. Vista “Statistics”. Observese que el coeficiente de variación es del 9%. : 7 =
  • 74. = > 8 ! % > = = = 7 8 = 7 1 ! : J : & K 8 > = ; 7 > 8 ; 7 = $ > ) 1 ( ) = ) = 7 L& M= WD1233> = ; 7 = E@>2X = 6 = ; = : ; 1 Ilustración 53 . “Frequency chart” del ejemplo
  • 75. 14.1.2. Matriz de correlación Ilustración 54 Matriz de Correlación ) 6 ; = = > = = 7 U= > = 7 = 7 ; = = 6 = 7 1 = ; ; = ) 6 > A (6 7 7 = ( 7 $ ) ; 7 Cárdenas Héctor, Curso de Econometría, capitulo 2. Profesor de la Facultad de Ciencias Económicas de la Universidad Nacional de Colombia
  • 76. = L ; 6= 6= M> = 7 = 7 = Q= 8 = = /] @2>B2@4CEEC _ 3>3EACDFCB V@ _ 3>42F4442@ V2_ 3>4DBF4CFA VB - ; 67 6= V@ = 7 V2 6= 7 = 7 VB 6= 7 Q ; ) : ; 6= ) ; = ; 7 6= > > / = 7 = 7 ! ; 7 7 6 ; ) ; 6= = > ) ; 7 Q = = ) ; > = ; ; ) = = 1 7 C = 6 ) ; = 6= = 7 > 6 7 = > ) : @ = 6 ; 8 7 6 1 8 Mide el grado de asociación lineal entre la variable dependiente (endógena) y la independiente o exógena, eliminando el efecto de las demás variables del modelo
  • 77. ! = T = ; = = 7 6 ) ; > = 7 ; = > > = > 1 ( = 7 ; : = T ! - > = 7 = = > = 7 = = 1 > = = : 8 > ; = : = ) 7 1 7 = = = > $ 7 ; > = : 1 Ilustración 55 – Matriz de correlación 7 > ! ; 8 > = ) 1 Ejemplo ! 8 = * ; > = ; 7 = L > = 7 7 M ; 6= > Q 7 = = 1 7 T = 8 1 % 8 ! 7 > ; ! (6 ; : ! = 8 LK KM> 8 = > > = = 7 L D33M> LEEEM ! 1
  • 78. , 7 = 7 J K 7 L M1 = 7 = ; 7 DF1 Ilustración 56 Cuadro de EStadisticas ! - > 7 = 7 Q ; ;# = = = : ; ; = 8 = 1 ( $ > = > = 8 7 1 ( 7 2333 233@ 2332 233B ! 7 2333 @>333 3>233 3>B33 3>@33 ! 7
  • 79. 233@ @>333 3>@33 3>B33 ! 7 2332 @>333 3>433 ! 7 233B @>333 ( ; ) 8 ; ) > = ) ) = J K = = > 7 8 1 > 7 ! 1 7 = 7 > ) = 1 14.1.3. Cuadro Tornado Chart Ilustración 57 Asistente de Tornado Chart ( : = ; > # 7 > ) : = ; = > 7 = ) ; > ; > = = Q ; > ; = 1 = ) ; ; = 7 Q ) ; > : # ;# ; J= ; 7
  • 80. = K J = # K1 ( - : = = ; 7 `- !: ` = !: ) = ! ) 2D3 ; = : = : 1 Tornado Chart ( : = ; ; = = > = 7 = > $ = 7= 6 = 7 = ; > > ) ; = 7 ( : = ; ; ! > ; 8 ; > : ; 7 1 ; 7 ) ; = 7 Q= ; ) = = 7 $ ; ) 81 (6 = 7 = ; > 6 7 ; # = 1 6 = 7 = = ; > ; 7 U = 7 1 Spider Chart $ 6 6 = 7 = ) # ; = ; 1 ! = > = > ) ; ; ; = 7 Q ) : = ) $ ; = 7 1 Ejemplo: % 8 = ; ; : 8 ) # > = )
  • 81. = = 8 1 ; T ! - > - !: > = > ;8 L= @ BM1 ! ; L= 2 BM = 1 ! ) ; ) ; 1 ! 1 ( = B B ; = = L @3X E3XM T = L DM> = 6 L 8 = = 7 M ( = 7 = = 7 ( # - = = = ; 1 = 7 - !: = !: ! 1 : - !: = !: > 8 = = : 1
  • 82. Ilustración 58 - Tornado Chart Ilustración 59 - Spider Chart
  • 83. ( 8 = > 4 = = > ; > ; > = 7 ; ; = ; 81 - !: = !: ; ) : = ; ; = > = = = ; = 7 1 8 = : = 6 = = ; ; 8 > 6 @33X > 7 = ; = ; : = = ; 1 ( = ; ; ) 7 7 ; 1
  • 84. 14.2. Herramientas de Análisis 14.2.1. Bootstrap Ilustración 60 - Asistente para Bootstrap ( # ) ) 6 = 7 Q : ) ; 7 = 6 > = 1 : # ; > = ) = ; 7 > = = 7 1 ! ) = ; => = 6 > = ; ; > = 7 ; > = = # 1 7 ; 7 = ; = ; ; 1 (6 # = ( # = ; = # 7 T
  • 85. ( > = ; ) # 7 > 1 7 ; = 1 ( ) = # = ; = 7 6 = 7 ; 7 ; = > ; Q # 7 = ) > ) = 8 7 7 : ) # 7 1 14.2.2. El método de la Multisimulación ! = > ; 7 > = = 7 = = 7 = > ; 7 7 L M1 % = 7 = = = 7 = ; = 7 1 ( # 7 ) = ; = # > = # : > = ; 5 6 > U5: > Q = = ; 7 ) = : Q ; = = ; 7 1 ( ; = = ; > = 6 = > # = 8 > ) ; T = = ; = = = 1
  • 86. Ilustración 61 – Comparación única simulación vs. Multisimulación Fuente: Tools tutorial 14.3. Ejemplo: % = 8 = > ) = = ; > 7 ; 1 ( ) : ; ) = : ! Q = ; (6 ; : = 8 = = > = : ) = ; ! = 8 ) = 7 1
  • 87. Ilustración 62 – Vision general Modelo “Planta energia nuclear” ! - > = 7 = ; = ;8 ) 1 6 =# = = 7 > 7 = = 2 B ; ) # T 7 = ; = # ) = # 1 ! 1 ( = = B B = ) = T > = = D33 > $ 7 = 7 1 ! 1 T, = > = 1 = = 6 @X EEX> = 1
  • 88. % 7 ; = = > > 7 > > > < 7 Q = = = 6 > : 1 = ; = = = 7 = = ) = ) > ) ; = 1 Ilustración 63 – Frecuency chart para la variable “Mean” ! 7 L M 7 > = ; ; = ) ) 1 ( 6 7 ) Q = ; 7 > 7 > ; 7 ; 7 1 % = 8 > 6= ; = > $ 7
  • 89. 7 ( * <P ^ ! 7 , 3>C2 3>C2 3>32 3>33 3>33 B>3A 3>32 ! @>333 3>AC3 U 3>3EA U 3>3EA 3>3@4 U 3>@FB U 3>@2B @>333 U 3>3EC U 3>3EC U 3>2EB U 3>3FA U 3>@@E 7 ( @>333 @>333 U 3>@CF 3>@A2 3>EEE * @>333 U 3>@CF 3>@A2 3>EEE < P @>333 U 3>BFD U 3>@CF ^ @>333 3>@AD ! * 7 @>333 Ilustración 64
  • 90. 14.3.1. Tabla para la toma de decisiones Ilustración 65 - Asistente para la Tabla de decisiones ; 7 ) = > ) ; = = > 8 ; = = 1 + ; ; > = ; ) ; 7 ; = 7 1 ( : ; = 7 ; 7 ; 7 = 7 1 % ) ; 7 > ) = = 7 > 8; = 9 ! 1 + ; = 9 >
  • 91. ) : Q = ; J = 9 K = J K) ; ! : 7= = 7 > ; 1 E Ejemplo ! 8 ! 7 ; > ) ; 8 = 7 = ) ; = ; > 7 = ; 7 > = ; = 8 = 1 % ; : ; ! > TJ K = T 7 T > EEE1 • 7 ! > ; ; = = = : T, 1 • ! ^1 • = 7 ! - > ) = ; 7 > ;8 1 • ( 8 = 7 1 E ! ; ) : : = ; ! % 233312> 7 = 1
  • 92. • ! > = 7 = • ; 7 1 ! 1 ) = = = = ; 7 ) 1 ! 1 = ) = > $ ; > T = 7 L= ; ; D33M1 ! 1 L3>BFM L3>BFCCCCCEM L3>BAAAAAACM L3>BCFFFFFAM L3>BEDDDDDFM L3>43444444M L3>4@BBBBBBM L3>42222222M L3>4B@@@@@@M L3>44M % L@BD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE @ % L@BCBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE 2 % L@4@FF>FFFFAM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE B % L@4D33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE 4 % L@4CBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE D % L@D@FF>FFFFAM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE F % L@DD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE A % L@DCBB>BBBBBM 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE C % 3>C@ 3>C2 3>CB 3>C4 3>C4 3>CD 3>CF 3>CA 3>CC 3>CE E
  • 93. L@F@FF>FFFFAM % L@FD33M 3>C@ 3>C2 3>CB 3>C4 3>CD 3>CD 3>CF 3>CA 3>CC 3>CE @3 @ 2 B 4 D F A C E @3 : 8 7 = ; 7 ) ; 7 > = ; = = 7 1 % > = = ;# 7 > ) 7 7 = Q ; 6 : T = 8 7 ; ; 7 > : = > 1 % 7 = T = 7 ; > $ > ) 6= # > ) L > > 1M = = 7 7= J ; 7 K> > ) = ; > 7 ) = = > ) 8 = ; 1
  • 94. = = ) $ ! = ; 7 = ; U = $ = = = ; 7 *1 1 = ; 7 > ! = 7 = * = = 7 = G ; ; H > G > 7 (6 ; > = 7 ; > ; > = a G 8 = 6= = ; G( H > ; 7 > = > = > = ; = ; 7
  • 95. ; 7 742 > = ; 7 ) = ; > ) 7 8 8 = 8 = > 8 ; 7 ; @D31 % = ; 7 > 7 J, K 8 > ; % 7 1 ( ) = = ; > : 1 14.3.2. Análisis de escenario Ilustración 66 - Asistente para el análisis de escenario ( = = = 7 > ) ! = 7 ; = 7 > = = > = = L@XM ) = = EE = ; 8 L@X1M % = 7 > ) = > ) = : ) # = ; 1 Ejemplo J= K> ; : = = = > ; 8 = = > = ; > = = Q : = )
  • 96. = 8 7 = > = = = = ) 1 ! = ; ! ; : : ( > 7 = 6= 7 = ) ; ( = = ; : 7 = (6 > : T ! - > ! Q = ;8 = 7 7 1 ! 1 ( 7 = 7 > = ) = = 3 @33 = 1 8 7 > = = ;8 = 7 1 % 7 ; ) @333 T 6 = > = 233B> ) 8 = ; = 1 / ; T = 1 , 8 = ) ; 8 = = 7 : > @333 = = 7 Q ) = 3 @33> = ; @333 = 7 > = : Q ; = ) ! 7= 1 = ) 8 J ( K = 7 ; = ) : = 7 Q ; 6 = = ; > ; = 3 : @331 % > = = = = =# 76 1 % = 7 > = ) = = = =
  • 97. (6 EA (6 23331 ( ) ) = ) ; 8 ! (6 EA 2333> ; ; = > ) = ; = 1 % 8 = = = 7 > 1 = : = 7 : 1 ( = > ) 1 ( ) > = = 7 ; ) % > 8 = 7 = > = = ; = = > ) 7 > ) = 7 1 A1 9 = = ; 1 ,< -7L!M -$= , !7 = 3>3@X 3>AD BBE@4EF>3DF BEEE>ED3FE DX 22X 3>32X 3>AD DEED@FE>42B BEEE>EC242A DX 22X 3>3BX 3>AD 4F2BA4F>@B@ BEEE>E23@BE DX 22X
  • 98. 3>34X 3>AF D2C2BCB>3@E 4333>@3EAD DX 2@X 3>3DX 3>AF 444CF4D>AAA BEEE>ECFC34 DX 2@X 3>3FX 3>AF 4AA3B4F>ADD BEEE>E4D@ FX 2@X 3>3AX 3>AF DCA@@BA>C4D BEEE>EAEBCD DX 2@X 3>3CX 3>AF 4B3B@@@>AB@ 4333>@3@F2F DX 2@X 3>3EX 3>AF D4F4C2E>@CA BEEE>E3342F 4X 2@X 3>@3X 3>AF 4E3B@24>@2A 4333>@@BBCB DX 2@X 3>@@X 3>AF 4EACAB4>FA4 4333>344ED 4X 2@X 3>@2X 3>AF D@@4C24>BDC BEEE>E4B3FD DX 2@X 3>@BX 3>AF 44CFD@3>CFD BEEE>CCE242 FX 2@X 3>@4X 3>AF 4D@ABFF>E32 BEEE>CDFFE2 FX 2@X 3>@DX 3>AF D2F24@F>E4F 4333>3B2CEF FX 2@X 3>@FX 3>AF BCD2@BE>C 4333>342D4C DX 2@X @>FDX 3>AC D4ABE@A>4EF 4333>34BEC4 DX @EX @>FFX 3>AC DDDBECE>42A BEEE>E2DCAD DX @EX @>FAX 3>AC DD3D32B>4D@ BEEE>EE3D4B DX @EX @>FCX 3>AC D22EDDD>E42 4333>3D4CE@ DX @EX @>FEX 3>AC 4CF4AEF>23B BEEE>E@4BF2 DX @EX @>A3X 3>AC 4CE3F43>F2D BEEE>EA@E3@ DX @EX @>A@X 3>AC 4FEE2@D>B2B BEEE>E3BFCE 4X @EX @>A2X 3>AC D3D4AFF>EC2 4333>@AEBEE DX @EX @>ABX 3>AC DFCBF33>AF@ 4333>2@@3FA 4X @EX @>A4X 3>AC 4AC33A4>E4 4333>@@@CE4 DX @EX @>ADX 3>AC 44CC3FA>2D4 BEEE>E3F4C DX @EX @>AFX 3>AC DDE2CD3>EA4 4333>3F22@F DX @EX @>AAX 3>AC 4@E3D4B>3EA 4333>@@@DDF DX @EX
  • 99. @>ACX 3>AC D3@@BC@>EDF 4333>3D33E FX @EX @>AEX 3>AC DC2@42E>A4B 4333>@4DACA DX @EX @>C3X 3>AC 4FE@D4C>4DC 4333>3DE@D2 DX @EX @>C@X 3>AC 423@@C4>E42 4333>2B@BAA DX @EX @>C2X 3>AC 4A4B43B>22 BEEE>E4ABE@ 4X @EX @>CBX 3>AC D@2ABCB>EB4 4333>3DE@CD FX @EX @>C4X 3>AC DB2DD34>BF2 4333>@2DF4E DX @EX @>CDX 3>AC BFAFD3B>3F@ BEEE>CCE4CE DX @EX @>CFX 3>AC 4CEA@AA>B2F 4333>3BA3A DX @EX @>CAX 3>AC D3D2@F4>4AF BEEE>AE24DE DX @EX @>CCX 3>AC 43AC244>2FC BEEE>EB@@@@ FX @EX @>CEX 3>AC 4DEB3C3>B@2 BEEE>E@34F4 DX @EX @>E3X 3>AC 42D2@DF>B3@ BEEE>E4D3FF DX @EX @>E@X 3>AC DDBED@E>F BEEE>ACAAAF 4X @EX @>E2X 3>AC DCC44F4>@@@ BEEE>EAAFFA DX @EX @>EBX 3>AC D@CEBD2>E4D 4333>@4F@FA DX @EX @>E4X 3>AC F4ADCF@>3@C 4333>3@3CDA DX @EX @>EDX 3>AC 4FA33D@>44E 4333>3DF4@D FX @EX @>EFX 3>AC 4DBF@BA>A@E 4333>33FAAD DX @EX @>EAX 3>AC 44DBA33>FD@ 4333>3CB424 FX @EX ( = ) Q ) ) = 7 = > = ; ; ) ) ) = 7 ) 7 = = =
  • 100. 14.3.3. Simulación bidimensional Ilustración 67 - Asistente para la simulación bidimensional ; 7 ; = ; = = ; ; ) = ) ; 7 = ; 1 ( = = ) = ; 7 1 ( 7 ; = = 1 * ; ( ; > > = $ ;
  • 101. ; ) #6 ) = Q 7 = ) = 7 > ) = ; 7 = ; 1 ; = ; ; = ; 7 > ; = 1 % : = > = ; ; @3 > = 7 = ; 7 = 7 = = ; = ; 7 1 ( : ; 8 7 > = = = ; ; Q 7 ; 8 ) 7 = 1 ( = 7 ; > ) = = ; = ; 7 1 Ejemplo = : ) ) ; ) ! 8 > = ) = : 8 = 8 : 1 10 Hoffman, F. O. and J. S. Hammonds. “Propagación de la incertidumbre en situaciones de riesgo: La necesidad de distinguir entre incertidumbre debida a la falta de conocimiento y la incertidumbre ocasionada por la variabilidad” Análisis de Riesgo, vol. 14, no. 5. pp 707-712, 1994.
  • 102. ( = = = 7 ; Q = : : 7 > (6 ; : 7 = > ; = : J, K 8 7 = = 7 T EEE> 7 ! ( T! - T = 7 : > ; = 7 7 ; > ;8 1 ! ;8 ) = $ > = 7 1 ! 1 = 1 = - $ = 7 Q > = = % = 8 7 = @33 = @>333 > = 1 : : = ; 7 = = ; 1 : = 7 = 7 ; = 7 1
  • 103. ,< L@M ,< L2M ,< LBM ,< L4M ,< LDM ,< LFM ,< LAM 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 = - 7 L! M 4AA323@>FEE 4D33B@4>@B D32CEB4>CC@ D@AAD23>FB4 DAD2A3C>C3F DAF@CAB>FE2 4C2DD32>C@2 D , FX DX DX DX DX 4X DX F 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 3>32 3>32 3>32 3>32 3>32 3>32 3>32 3 * 3>33 3>33 3>33 3>33 3>33 3>33 3>33 3 < P U3>@3 3>@2 U3>3B U3>3E U3>3E U3>32 U3>@@ 3 ^ 2>EA B>2A 2>A3 2>ED 2>CA B>BB 2>C2 2 ! 1 * ; 3>32 3>32 3>32 3>3B 3>32 3>32 3>32 3 3>AD 3>AF 3>AD 3>A4 3>A4 3>AD 3>AF 3 6 3>CA 3>CE 3>CC 3>CE 3>CC 3>CE 3>CE 3 , 3>@2 3>@B 3>@B 3>@4 3>@4 3>@4 3>@B 3 % DXU 3>AE 3>AC 3>AE 3>AE 3>AE 3>AE 3>AE 3
  • 104. @3XU 3>AE 3>AE 3>AE 3>AE 3>AE 3>AE 3>AE 3 @DXU 3>C3 3>C3 3>C3 3>C3 3>C3 3>C3 3>C3 3 23XU 3>C3 3>C3 3>C3 3>C3 3>C3 3>C3 3>C3 3 2DXU 3>C3 3>C@ 3>C3 3>C3 3>C@ 3>C@ 3>C@ 3 B3XU 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3 BDXU 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3 43XU 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3>C@ 3 4DXU 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 D3XU 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 DDXU 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 F3XU 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3>C2 3 FDXU 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3 A3XU 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3 ADXU 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3>CB 3 C3XU 3>CB 3>CB 3>C4 3>C4 3>C4 3>CB 3>C4 3 CDXU 3>C4 3>C4 3>C4 3>C4 3>C4 3>C4 3>C4 3 E3XU 3>C4 3>C4 3>C4 3>C4 3>CD 3>C4 3>C4 3 EDXU 3>CD 3>CD 3>CD 3>CD 3>CD 3>CD 3>CD 3
  • 105. %2 # - ) @3D = ; = 7 > = ; > L = M ; 7 1 Ilustración 68 - Overlay Chart ( # = 7 = = = > ) : :
  • 106. %2 # - ) @3F Ilustración 69 - Grafico de tendencias T = ) $ = = = > ; = ; ; > ; ) ; : 1 : = $ = = = = ; = ; 1 ( = ; = 7 = ) = 7 = 7 L @X : EEXM1
  • 107. %2 # - ) @3A Ilustración 70 - Trend Chart = = ) 8 : 8 7 > = ) 8 # ) = : ! > = 8 > ; 8 #6 7 ) ; ; = ; 1 15. BIBLIOGRAFÍA Y WEBGRAFÍA • (* + > " , 0 + QJ3 4 KQ@ECCU 2334> > 1Q% 1 @U234 • - J = , :1 KQF : ( Q ( 1 % Q@EEAQ% 1 @UFA • +> ": : Q J== , < 1 K> ( 1 ": 5 233B1 ! , 1