Probabilidad

Es el estudio de azar o incertidumbre en cualquier situación en la cual varios posibles sucesos pueden ocurrir.

Es un valor entre 0(imposible) y 1(seguro).
Ejemplo: la probabilidad de que llueva hoy es de 0.70 (70%).

Experimento: Cualquier acción cuyo resultado está sujeto a la incertidumbre.
Ejemplo: lanzar una modeda al aire.

Experimento: lanzar un dado.

Librerias

library(dice)
library(MASS)
library(purrr)

¿Cuál es la probabilidad de obtener un 6 al lanzar un dado?

un_seis<-getEventProb(nrolls = 1, ndicePerRoll = 1, nsidesPerDie = 6, eventList = list(1:2))
un_seis
## [1] 0.3333333
fractions(un_seis)
## [1] 1/3

¿Cuál es la probabilidad de sumar 5 al lanzar dos dados?

un_cinco<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(5))
un_cinco
## [1] 0.1111111
fractions(un_cinco)
## [1] 1/9

¿Cuál es la probabilidad de obtener cinco en dos lanzamientos de dados consecutivos?

dos_cincos<-getEventProb(nrolls = 2, ndicePerRoll = 1, nsidesPerDie = 6, eventList = list(5,5))
dos_cincos
## [1] 0.02777778
fractions(dos_cincos)
## [1] 1/36

¿Qué número es más probable de alcanzar al lanzar dos dados?

sumar_dos<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(2))
sumar_tres<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(3))
sumar_cuatro<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(4))
sumar_cinco<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(5))
sumar_seis<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(6))
sumar_siete<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(7))
sumar_ocho<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(8))
sumar_nueve<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(9))
sumar_diez<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(10))
sumar_once<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(11))
sumar_doce<-getEventProb(nrolls = 1, ndicePerRoll = 2, nsidesPerDie = 6, eventList = list(12))

suma<-c(2,3,4,5,6,7,8,9,10,11,12)
probabilidad<-c(sumar_dos,sumar_tres,sumar_cuatro,sumar_cinco,sumar_seis,sumar_siete,sumar_ocho,sumar_nueve,sumar_diez,sumar_once,sumar_doce)

tabla<-cbind(suma,probabilidad)

barplot(probabilidad, names.arg = suma, main = "Probabildiad", xlab = "Suma de 2 dados", col = "Tomato")

Experimento Mano de Poker

Crear baraja inglesa

palo<-c("Picas", "Corazones", "Diamantes", "Treboles")
palos<-rep(palo,13)
numero<-c( "A",2, 3, 4, 5, 6, 7, 8, 9, "D", "J", "Q", "K")
numeros<-rep(numero,4)
baraja<-cbind(palos,numeros)
baraja
##       palos       numeros
##  [1,] "Picas"     "A"    
##  [2,] "Corazones" "2"    
##  [3,] "Diamantes" "3"    
##  [4,] "Treboles"  "4"    
##  [5,] "Picas"     "5"    
##  [6,] "Corazones" "6"    
##  [7,] "Diamantes" "7"    
##  [8,] "Treboles"  "8"    
##  [9,] "Picas"     "9"    
## [10,] "Corazones" "D"    
## [11,] "Diamantes" "J"    
## [12,] "Treboles"  "Q"    
## [13,] "Picas"     "K"    
## [14,] "Corazones" "A"    
## [15,] "Diamantes" "2"    
## [16,] "Treboles"  "3"    
## [17,] "Picas"     "4"    
## [18,] "Corazones" "5"    
## [19,] "Diamantes" "6"    
## [20,] "Treboles"  "7"    
## [21,] "Picas"     "8"    
## [22,] "Corazones" "9"    
## [23,] "Diamantes" "D"    
## [24,] "Treboles"  "J"    
## [25,] "Picas"     "Q"    
## [26,] "Corazones" "K"    
## [27,] "Diamantes" "A"    
## [28,] "Treboles"  "2"    
## [29,] "Picas"     "3"    
## [30,] "Corazones" "4"    
## [31,] "Diamantes" "5"    
## [32,] "Treboles"  "6"    
## [33,] "Picas"     "7"    
## [34,] "Corazones" "8"    
## [35,] "Diamantes" "9"    
## [36,] "Treboles"  "D"    
## [37,] "Picas"     "J"    
## [38,] "Corazones" "Q"    
## [39,] "Diamantes" "K"    
## [40,] "Treboles"  "A"    
## [41,] "Picas"     "2"    
## [42,] "Corazones" "3"    
## [43,] "Diamantes" "4"    
## [44,] "Treboles"  "5"    
## [45,] "Picas"     "6"    
## [46,] "Corazones" "7"    
## [47,] "Diamantes" "8"    
## [48,] "Treboles"  "9"    
## [49,] "Picas"     "D"    
## [50,] "Corazones" "J"    
## [51,] "Diamantes" "Q"    
## [52,] "Treboles"  "K"

Crear el mazo de barajas

mazo<-apply(format(baraja),1,paste,collapse="")
mazo
##  [1] "Picas    A        " "Corazones2        " "Diamantes3        "
##  [4] "Treboles 4        " "Picas    5        " "Corazones6        "
##  [7] "Diamantes7        " "Treboles 8        " "Picas    9        "
## [10] "CorazonesD        " "DiamantesJ        " "Treboles Q        "
## [13] "Picas    K        " "CorazonesA        " "Diamantes2        "
## [16] "Treboles 3        " "Picas    4        " "Corazones5        "
## [19] "Diamantes6        " "Treboles 7        " "Picas    8        "
## [22] "Corazones9        " "DiamantesD        " "Treboles J        "
## [25] "Picas    Q        " "CorazonesK        " "DiamantesA        "
## [28] "Treboles 2        " "Picas    3        " "Corazones4        "
## [31] "Diamantes5        " "Treboles 6        " "Picas    7        "
## [34] "Corazones8        " "Diamantes9        " "Treboles D        "
## [37] "Picas    J        " "CorazonesQ        " "DiamantesK        "
## [40] "Treboles A        " "Picas    2        " "Corazones3        "
## [43] "Diamantes4        " "Treboles 5        " "Picas    6        "
## [46] "Corazones7        " "Diamantes8        " "Treboles 9        "
## [49] "Picas    D        " "CorazonesJ        " "DiamantesQ        "
## [52] "Treboles K        "

Crear mano de cartas

mano<-function(n) sample(mazo,n,rep=FALSE)
mi_mano<-mano(5)
mi_mano
## [1] "Treboles A        " "Corazones7        " "Treboles 9        "
## [4] "Treboles D        " "DiamantesD        "
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