13.1.5 - Common Probability Density Functions
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What does a Probability Density Function (PDF) represent?
💡 Hint: Think about how continuous variables behave.
Is the probability at a single point for a continuous random variable zero?
💡 Hint: Consider the infinite possibilities in a continuous range.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does the total area under the PDF curve equal?
💡 Hint: Consider the definition of probability.
True or False: In a continuous distribution, the probability of a single point is greater than zero.
💡 Hint: Think about the concept of continuous values.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
A continuous random variable has a PDF defined as f(x) = kx for 0 ≤ x ≤ 2, where k is a constant. Find k and then calculate P(0.5 ≤ X ≤ 1.5).
💡 Hint: Remember to first find k by normalization.
Given a Normal distribution with mean of 100 and standard deviation of 15, what is the probability of selecting a value between 85 and 115?
💡 Hint: Calculate Z-scores from the provided values and refer to the Z-table.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.