Is This a Poisson or Binomial Random Variable?

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In summary, the conversation discusses the use of Poisson and binomial random variables in solving a problem. The poster is unsure if the given equations are Poisson or binomial and is seeking clarification on how to show the relationship between x and y. A formula for calculating P(X=x and Y=y) is also mentioned.
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lordy12
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1. http://d.imagehost.org/t/0866/problem1.jpg



Homework Equations





3. For the Poisson random variables I get ((lamda)^x)/((e^2lambda)*x!) when y =1. Is this a Poisson Random variable? Also, when y = 0, I get ((lamda)^x)/((e^lambda)*x!) - ((lamda)^x)/((e^2lambda)*x!) I cannot get the binomial. I don't know how to show that this is Binomial as x is in the range from 1...infinity.

For part 1 I used the fact that P(X=x and Y=y) = P(X|Y)P(Y)
and P(Y=y) = sum(1 to x)P(X=x and Y=y) = 1, so P(X=x|Y=y)(P(y) = P(X=x and Y=y)
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http://d.imagehost.org/view/0752/problem1.jpg
 
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1. What is the definition of probability?

Probability is a measure of the likelihood of an event occurring. It is a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.

2. How do you calculate probability?

To calculate probability, you divide the number of favorable outcomes by the total number of possible outcomes. This is known as the classical definition of probability.

3. What is the difference between theoretical and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability is based on actual data collected from repeated trials of an experiment.

4. What is the difference between independent and dependent events?

Independent events are events that do not affect each other's probabilities. For example, flipping a coin twice. Dependent events are events where the outcome of one event affects the probability of the other event. For example, drawing two cards from a deck without replacement.

5. How can you use probability in real life?

Probability is used in many real-life situations, such as weather forecasting, sports betting, and risk assessment in insurance and finance. It can also be used to make informed decisions and predictions based on data and likelihood of certain outcomes.

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