Practice Common Discrete Distributions And Their Pmfs (12.9)

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6 sample questions

Question 1.
Define a discrete random variable with an example.
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Think of countable items.
Question 2.
What does PMF stand for and what does it represent?
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What does probability relate to in regards to outcomes?
3Question 3.
What is the PMF of a Bernoulli distribution?
- p^x(1 - p)^{1 - x}
- p(1 - p)^x
- (n choose x)p^x(1 - p)^{n - x}
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Remember the two outcomes of Bernoulli.
4Question 4.
True or False: The Poisson distribution can be used for modeling continuous random variables.
- True
- False
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Consider the type of variable it models.
Question 5.
Consider a biased coin, where the probability of heads is 0.7. If you toss it 10 times, calculate the probability of getting exactly 7 heads.
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You'll need to calculate the binomial coefficient.
Question 6.
A radio station receives an average of 5 calls per hour. What is the probability that it will receive exactly 3 calls in the next hour?
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Apply the Poisson formula directly.

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