Chapter 3 HW- Probability Topics Current score: AI. Category: Homework 68.95/100 points d. Which of the following explains what " \( P(A \mid B) \) " represents? A \( P(A \mid B) \) is the probability that the sum of rolling two dice is at most ten given the fact that we have a one or three on the first die, followed by an odd number on the second die. B \( P(A \mid B) \) is the probability of rolling a one or three on the first die, followed by an odd number on the second die given that the sum of these two rolls is at least ten. C \( P(A \mid B) \) is the probability of rolling a one or three on the first die, followed by an odd number on the second die given that the sum of these two rolls is at most ten. D None of the above Find \( P(A \mid B) \). \[ P(A \mid B)= \] Enter your answer e. Are \( A \) and \( B \) mutually exclusive events? It is possible to have a one or a three on the first die rolling followed by an odd number on the second die when the sum of these two numbers is A at most ten. Numerically, we have \( P(A \) AND \( B)=\frac{1}{6} \), so the events are not mutually exclusive. It is impossible to have a one or a three on the first die rolling followed by an odd number on the second die when the sum of these two numbers \( B \) is at most ten. Numerically, we have \( P(A \) AND \( B)=0 \), so the events are mutually exclusive.
Solución de tutoría real
Responder
Solución
¡Inicia sesión para desbloquear respuestas gratis!
Una plataforma de aprendizaje en la que confían millones de estudiantes y profesores reales.
Revisado y aprobado por el equipo de tutoría de UpStudy
Extra Insights
When dealing with conditional probabilities like \( P(A \mid B) \), it's important to remember that it represents the likelihood of event A occurring when event B has already occurred. In this case, if B is our condition (e.g., having a one or three on the first die and an odd number on the second), we need to consider the sample space defined by B when calculating probabilities for A. This is a fun way to explore how different outcomes can be inferred based on prior information! To calculate \( P(A \mid B) \), you will first need to know the total number of outcomes in event B and determine how many of these outcomes also satisfy event A. To put it simply, count the successful outcomes for A within the context of B and then divide it by the total outcomes of B! This way, you’ll find the concentrated probability without getting lost in the sea of possibilities. Happy calculating!