Practice Definitions and Basics - 14.1 | 14. Joint Probability Distributions | Mathematics - iii (Differential Calculus) - Vol 3
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Definitions and Basics

14.1 - Definitions and Basics

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define a discrete random variable with an example.

💡 Hint: Think of something that can be counted.

Question 2 Easy

What is a joint probability distribution?

💡 Hint: Consider how two dice rolls might relate.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a random variable?

💡 Hint: Remember the connection to probability outcomes.

Question 2

For discrete random variables, what must the joint pmf always satisfy?

Must be negative
Must equal to 2
Must sum up to 1

💡 Hint: Think about the total probability.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a joint pmf for two discrete random variables X and Y, calculate the marginal pmfs and check independence from the provided joint distribution.

💡 Hint: Look for the sums to equal 1 and the independence equalities.

Challenge 2 Hard

We have X ~ N(0, σ²) and Y ~ N(0, σ²) as jointly normal random variables. Show that X and Y being uncorrelated implies independence.

💡 Hint: Remember the special properties of the normal distribution.

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