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3 cards from this section. Quick, good the night before a test.
What does PDF stand for?
Recall the acronym we discussed.
What property ensures the area under a PDF equals one?
Think about the key requirements of a PDF.
What property must a PDF satisfy?
Consider what makes a valid probability distribution.
Is the mean of a random variable always zero?
Think about different types of distributions.
Given a continuous random variable with PDF f(x) = 12x(1-x) for 0 ≤ x ≤ 1, find the probability that X falls between 0.25 and 0.75.
Refer to integration techniques for polynomials.
Calculate the expected value (mean) of X when its PDF is given as f(x) = 6x(1-x) for 0 ≤ x ≤ 1.
Distributing and integrating will be key here.
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