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3 cards from this section. Quick, good the night before a test.
What is a discrete random variable? Provide an example.
Think of variables that can be counted easily.
What is one property of a PDF?
Think about the chances of probability being negative.
What type of random variable can take on countable values?
Think about whether the values can be counted.
True or False: The total area under a PDF is always equal to one.
Consider how probabilities sum up across all outcomes.
Given a PDF defined as f(x) = 1/3 for 0 ≤ x ≤ 3 and 0 otherwise, calculate P(1 ≤ X ≤ 2).
Use the integral of the PDF over the specified interval.
For a continuous variable with mean μ and variance σ², derive the PDF for the normal distribution.
Consider the characteristics of normal distributions and their symmetrical properties.
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