94:@0.058599:0.966558:0.074760:0.966558:0.074760:0.950778:0.058599:0.950778:0.000000:0.000000
Distribución de Poisson X: Ps( ):@0.404235:0.118449:0.805186:0.118449:0.805186:0.073790:0.404235:0.073790:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
λ:@0.766438:0.117657:0.794029:0.117657:0.794029:0.071451:0.766438:0.071451:0.000000
M.5.3.18. Identificar variables aleatorias discretas en problemas de texto y reconocer la distribución de Poisson, como ejemplo de variables aleatorias discretas y sus :@0.148948:0.939630:0.888514:0.939630:0.888514:0.929588:0.148948:0.929588:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
aplicaciones.:@0.148948:0.948432:0.203417:0.948432:0.203417:0.938389:0.148948:0.938389:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Para comprender mejor esta distribución, vamos a analizar el siguien-:@0.404236:0.146953:0.891822:0.146953:0.891822:0.130455:0.404236:0.130455:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
te caso. Supongamos que tenemos una tabla rectangular cuya super-:@0.404236:0.164303:0.891763:0.164303:0.891763:0.147806:0.404236:0.147806:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
ficie se encuentra pintada; al observarla fijamente, es posible detectar :@0.404236:0.181654:0.895939:0.181654:0.895939:0.165157:0.404236:0.165157:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
pequeños defectos. Se desea determinar la probabilidad de que apa-:@0.404236:0.199005:0.891717:0.199005:0.891717:0.182507:0.404236:0.182507:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
rezcan estos defectos y, para ello, se divide la superficie en otras de :@0.404236:0.216356:0.895859:0.216356:0.895859:0.199858:0.404236:0.199858:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
igual tamaño, como muestra la Figura 3.19.:@0.404236:0.233706:0.706583:0.233706:0.706583:0.217209:0.404236:0.217209:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Defectos:@0.426626:0.281240:0.478123:0.281240:0.478123:0.266994:0.426626:0.266994:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Observamos que en unas zonas aparece el defecto y en otras no. :@0.404236:0.422431:0.895941:0.422431:0.895941:0.405933:0.404236:0.405933:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 :@0.891763:0.422431:0.895905:0.422431:0.895905:0.405933:0.891763:0.405933:0.000000
Supongamos que en cada zona solo aparece un defecto. Entonces, :@0.404236:0.439782:0.895861:0.439782:0.895861:0.423284:0.404236:0.423284:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
podemos utilizar la distribución binomial para calcular la probabili-:@0.404236:0.457133:0.891799:0.457133:0.891799:0.440635:0.404236:0.440635:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
dad de que en la superficie en mención aparezcan 0, 1, 2, 3, 4 defectos.:@0.404236:0.474483:0.891757:0.474483:0.891757:0.457986:0.404236:0.457986:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
B n k:@0.539165:0.514958:0.578717:0.514958:0.578717:0.498490:0.539165:0.498490:0.000000:0.000000:0.000000:0.000000:0.000000
,:@0.566329:0.514843:0.569084:0.514843:0.569084:0.498345:0.566329:0.498345:0.000000
( ):@0.548902:0.517778:0.586411:0.517778:0.586411:0.495799:0.548902:0.495799:0.000000:0.000000:0.000000
=:@0.589109:0.515479:0.599686:0.515479:0.599686:0.499198:0.589109:0.499198:0.000000
k:@0.614866:0.522436:0.623223:0.522436:0.623223:0.505743:0.614866:0.505743:0.000000
4:@0.614866:0.508411:0.623477:0.508411:0.623477:0.491689:0.614866:0.491689:0.000000
p:@0.648684:0.505686:0.657950:0.505686:0.657950:0.489217:0.648684:0.489217:0.000000
4:@0.648530:0.525769:0.657026:0.525769:0.657026:0.509272:0.648530:0.509272:0.000000
k:@0.669834:0.495479:0.674606:0.495479:0.674606:0.485947:0.669834:0.485947:0.000000
1:@0.686796:0.514843:0.695291:0.514843:0.695291:0.498345:0.686796:0.498345:0.000000
p:@0.711663:0.505686:0.720929:0.505686:0.720929:0.489217:0.711663:0.489217:0.000000
4:@0.711509:0.525769:0.720005:0.525769:0.720005:0.509272:0.711509:0.509272:0.000000
4:@0.732813:0.495412:0.737730:0.495412:0.737730:0.485863:0.732813:0.485863:0.000000
k:@0.744382:0.495479:0.749154:0.495479:0.749154:0.485947:0.744382:0.485947:0.000000
.:@0.752653:0.514843:0.755407:0.514843:0.755407:0.498345:0.752653:0.498345:0.000000
Ahora bien, en una zona podría aparecer más de un defecto, por lo :@0.404236:0.558345:0.895880:0.558345:0.895880:0.541848:0.404236:0.541848:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
que el cálculo es inexacto. Para corregir este error, debemos subdivi-:@0.404236:0.575696:0.891740:0.575696:0.891740:0.559198:0.404236:0.559198:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
dir el área en varias regiones de tal manera que podamos obtener el :@0.404236:0.593047:0.895924:0.593047:0.895924:0.576549:0.404236:0.576549:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
límite de la fórmula de la distribución binomial y obtener la fórmula :@0.404236:0.610398:0.895899:0.610398:0.895899:0.593900:0.404236:0.593900:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de Poisson.:@0.404236:0.627748:0.482723:0.627748:0.482723:0.611251:0.404236:0.611251:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Características de la distribución de Poisson :@0.404236:0.663847:0.759888:0.663847:0.759888:0.646165:0.404236:0.646165:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
X Ps:@0.763605:0.662793:0.800344:0.662793:0.800344:0.646324:0.763605:0.646324:0.000000:0.000000:0.000000:0.000000
::@0.774606:0.662677:0.777361:0.662677:0.777361:0.646180:0.774606:0.646180:0.000000
( ):@0.800879:0.665613:0.826772:0.665613:0.826772:0.643633:0.800879:0.643633:0.000000:0.000000:0.000000
.:@0.827683:0.662677:0.830438:0.662677:0.830438:0.646180:0.827683:0.646180:0.000000
La distribución de Poisson de una variable aleatoria   y parámetro :@0.404236:0.681184:0.874940:0.681184:0.874940:0.664686:0.404236:0.664686:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
X:@0.769908:0.681299:0.779868:0.681299:0.779868:0.664831:0.769908:0.664831:0.000000
se representa con la notación:@0.404236:0.698534:0.612973:0.698534:0.612973:0.682037:0.404236:0.682037:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
X Ps:@0.617377:0.733453:0.654116:0.733453:0.654116:0.716985:0.617377:0.716985:0.000000:0.000000:0.000000:0.000000
::@0.628377:0.733338:0.631132:0.733338:0.631132:0.716840:0.628377:0.716840:0.000000
( ):@0.654653:0.736273:0.680545:0.736273:0.680545:0.714294:0.654653:0.714294:0.000000:0.000000:0.000000
.:@0.681457:0.733338:0.684211:0.733338:0.684211:0.716840:0.681457:0.716840:0.000000
Propiedades:@0.404236:0.759222:0.499482:0.759222:0.499482:0.742276:0.404236:0.742276:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
::@0.499484:0.758976:0.502836:0.758976:0.502836:0.742261:0.499484:0.742261:0.000000
•  Se aplica a una población de tamaño infinito.:@0.404236:0.776110:0.748464:0.776110:0.748464:0.759612:0.404236:0.759612:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
•  Los sucesos son independientes entre sí.:@0.404236:0.793461:0.711687:0.793461:0.711687:0.776963:0.404236:0.776963:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
•  La distribución de Poisson parte de la distribución binomial.:@0.404236:0.810811:0.851435:0.810811:0.851435:0.794314:0.404236:0.794314:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
•  Cuando en una distribución binomial se realiza el experimento :@0.404236:0.828162:0.895963:0.828162:0.895963:0.811664:0.404236:0.811664:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
muchas veces, la muestra  es grande y la probabilidad de éxito :@0.427971:0.845513:0.895957:0.845513:0.895957:0.829015:0.427971:0.829015:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 n:@0.611914:0.845629:0.626748:0.845629:0.626748:0.829160:0.611914:0.829160:0.000000:0.000000
en cada ensayo es baja. Es aquí cuando se aplica la distribución de :@0.427971:0.862864:0.895859:0.862864:0.895859:0.846366:0.427971:0.846366:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Poisson.:@0.427971:0.880214:0.484455:0.880214:0.484455:0.863717:0.427971:0.863717:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
•  El  producto de :@0.404236:0.897565:0.544227:0.897565:0.544227:0.881067:0.404236:0.881067:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
np:@0.547290:0.897681:0.565766:0.897681:0.565766:0.881212:0.547290:0.881212:0.000000:0.000000
  tiende  a  aproximarse  a un  valor  promedio, :@0.565737:0.897565:0.895903:0.897565:0.895903:0.881067:0.565737:0.881067:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 al que denominamos parámetro  .:@0.427971:0.914916:0.679072:0.914916:0.679072:0.898418:0.427971:0.898418:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
λ:@0.665741:0.914410:0.676317:0.914410:0.676317:0.896698:0.665741:0.896698:0.000000
Desequilibrio cognitivo:@0.199646:0.237886:0.363493:0.237886:0.363493:0.222413:0.199646:0.222413:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
¿Existe alguna relación :@0.199884:0.266513:0.347075:0.266513:0.347075:0.251450:0.199884:0.251450:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
entre distribución binomial :@0.153341:0.282355:0.333214:0.282355:0.333214:0.267292:0.153341:0.267292:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
y normal?:@0.153341:0.298197:0.216348:0.298197:0.216348:0.283134:0.153341:0.283134:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Saberes previos:@0.199646:0.115710:0.307805:0.115710:0.307805:0.100238:0.199646:0.100238:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
¿Cuál es la diferencia :@0.199884:0.144338:0.335643:0.144338:0.335643:0.129274:0.199884:0.129274:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
entre variable discreta y variable :@0.153341:0.160180:0.363188:0.160180:0.363188:0.145116:0.153341:0.145116:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
continua?:@0.153341:0.176022:0.216682:0.176022:0.216682:0.160958:0.153341:0.160958:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Recuerda la definición:@0.199646:0.364643:0.355597:0.364643:0.355597:0.349171:0.199646:0.349171:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
•   :@0.199884:0.394572:0.217646:0.394572:0.217646:0.378074:0.199884:0.378074:0.000000:0.000000:0.000000:0.000000
La distribución  :@0.217645:0.394251:0.321283:0.394251:0.321283:0.379188:0.217645:0.379188:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de Poisson es, junto con la :@0.169958:0.410093:0.344291:0.410093:0.344291:0.395030:0.169958:0.395030:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
distribución binomial, una de :@0.169958:0.425935:0.363411:0.425935:0.363411:0.410872:0.169958:0.410872:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
las más importantes distribu-:@0.169958:0.441777:0.358979:0.441777:0.358979:0.426714:0.169958:0.426714:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
ciones de probabilidad para :@0.169958:0.457619:0.353946:0.457619:0.353946:0.442556:0.169958:0.442556:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
variables discretas. Es decir, :@0.169958:0.473461:0.347211:0.473461:0.347211:0.458398:0.169958:0.458398:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
solo puede tomar valores 0, :@0.169958:0.489303:0.352557:0.489303:0.352557:0.474240:0.169958:0.474240:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
1, 2, 3, 4, …, k.:@0.169958:0.505145:0.256659:0.505145:0.256659:0.490082:0.169958:0.490082:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
• :@0.153346:0.538659:0.162824:0.538659:0.162824:0.522161:0.153346:0.522161:0.000000:0.000000
Utilizaremos la distribución :@0.169966:0.538338:0.350650:0.538338:0.350650:0.523275:0.169966:0.523275:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de Poisson como una apro-:@0.169966:0.554180:0.348028:0.554180:0.348028:0.539117:0.169966:0.539117:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
ximación del experimento :@0.169966:0.570022:0.343808:0.570022:0.343808:0.554959:0.169966:0.554959:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
binomial, donde el número :@0.169966:0.585864:0.350560:0.585864:0.350560:0.570801:0.169966:0.570801:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
de pruebas es muy alto :@0.169966:0.601706:0.323982:0.601706:0.323982:0.586643:0.169966:0.586643:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
n:@0.178307:0.617981:0.186733:0.617981:0.186733:0.603159:0.178307:0.603159:0.000000
(:@0.171899:0.620519:0.177673:0.620519:0.177673:0.600738:0.171899:0.600738:0.000000
):@0.222459:0.620519:0.228232:0.620519:0.228232:0.600738:0.222459:0.600738:0.000000
,:@0.229710:0.617877:0.232189:0.617877:0.232189:0.603029:0.229710:0.603029:0.000000
 pero con proba-:@0.234797:0.618428:0.344348:0.618428:0.344348:0.603365:0.234797:0.603365:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
bilidad de éxito muy baja :@0.169961:0.634270:0.337117:0.634270:0.337117:0.619207:0.169961:0.619207:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
p:@0.179342:0.653437:0.187682:0.653437:0.187682:0.638615:0.179342:0.638615:0.000000
0 .:@0.210203:0.653333:0.227854:0.653333:0.227854:0.638485:0.210203:0.638485:0.000000:0.000000:0.000000
(:@0.171899:0.655975:0.177673:0.655975:0.177673:0.636194:0.171899:0.636194:0.000000
):@0.218783:0.655975:0.224557:0.655975:0.224557:0.636194:0.218783:0.636194:0.000000
p:@0.822931:0.400983:0.834411:0.400983:0.834411:0.390959:0.822931:0.390959:0.000000
 :@0.834411:0.401691:0.837292:0.401691:0.837292:0.390215:0.834411:0.390215:0.000000
Figura 3.20.:@0.837292:0.401691:0.891771:0.401691:0.891771:0.390215:0.837292:0.390215:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000