1. Let´s consider the following random experiment. Suppose we have two jars: • Jar 1 has 5 white balls and 5 black balls. • Jar 2 has 3 white balls and 7 black balls. Assume you have a biased coin with P(Head) = ;. Take the coin and toss it, if it lands on heads draw 4 balls from jar 1, otherwise draw 4 balls from jar 2. Define the random variable X to be 1 if heads turns up and 0 otherwise. Also, define the random variable Y to be the total number of white balls in the sample drawn. First, let's assume that you are drawing the balls without replacement. Answer the following questions: (a) What is the conditional distribution of Y, given that the coin shows heads? You can give the PMF or, if it is a known distribution, you can provide its name and parameter values. (b) Find the joint PMF of (X;Y); you can express the PMF in a formula (clearly stating all values where the PMF is positive), or you can provide a table of probabilities. (c) Find the marginal PMF of Y. (d) Repeat part (a) assuming now the sampling is happening with replace-ment.

A First Course in Probability (10th Edition)
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Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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1. Let's consider the following random experiment. Suppose we have two jars:
• Jar 1 has 5 white balls and 5 black balls.
• Jar 2 has 3 white balls and 7 black balls.
Assume you have a biased coin with P(Head) = . Take the coin and toss it, if it lands
on heads draw 4 balls from jar 1, otherwise draw 4 balls from jar 2. Define the random
variable X to be 1 if heads turns up and 0 otherwise. Also, define the random variable
Y to be the total number of white balls in the sample drawn.
First, let's assume that you are drawing the balls without replacement. Answer the
following questions:
(a) What is the conditional distribution of Y, given that the coin shows heads?
You can give the PMF or, if it is a known distribution, you can provide its
name and parameter values.
(b) Find the joint PMF of (X;Y); you can express the PMF in a formula
(clearly stating all values where the PMF is positive), or you can provide a table of
probabilities.
(c) Find the marginal PMF of Y.
(d) Repeat part (a) assuming now the sampling is happening with replace-ment.
Transcribed Image Text:1. Let's consider the following random experiment. Suppose we have two jars: • Jar 1 has 5 white balls and 5 black balls. • Jar 2 has 3 white balls and 7 black balls. Assume you have a biased coin with P(Head) = . Take the coin and toss it, if it lands on heads draw 4 balls from jar 1, otherwise draw 4 balls from jar 2. Define the random variable X to be 1 if heads turns up and 0 otherwise. Also, define the random variable Y to be the total number of white balls in the sample drawn. First, let's assume that you are drawing the balls without replacement. Answer the following questions: (a) What is the conditional distribution of Y, given that the coin shows heads? You can give the PMF or, if it is a known distribution, you can provide its name and parameter values. (b) Find the joint PMF of (X;Y); you can express the PMF in a formula (clearly stating all values where the PMF is positive), or you can provide a table of probabilities. (c) Find the marginal PMF of Y. (d) Repeat part (a) assuming now the sampling is happening with replace-ment.
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