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3 cards from this section. Quick, good the night before a test.
What is a random variable?
Think of it as a representation of outcomes in numbers.
Define a discrete random variable.
Consider examples like dice rolls or number of students.
What is the normalization condition for a PDF?
Consider how probabilities relate to areas in geometry.
True or false: CDF can give the probability of a random variable being greater than a specific value.
Think about what CDF shows and what it doesn't.
A continuous random variable has a PDF defined as f(x) = kx for 0 ≤ x ≤ 2. Find the value of k and then the probability that X < 1.
Remember to normalize the PDF first, then use integration.
The mean of a random variable X is defined by the integral μ = ∫ x f(x) dx. For the PDF f(x) = 2x (0 ≤ x ≤ 1), calculate the mean.
The integration step is crucial for finding the expected value!
5 more questions in this section. Enroll free to practise them all.
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