Entropy, Joint and Conditional Entropy
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Each question is graded on a single answer: a check that this chapter's methods work, not a test of the reasoning behind them.
An event has probability . Give its surprisal in bits.
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info-information-theory-59All Information Theory chaptersAbout these 133 questions
What information means, how entropy measures it, and how entropy behaves when several random variables are considered together. This set covers the chapter Entropy, Joint and Conditional Entropy in Information Theory: 39 easy, 56 medium and 38 hard questions, each graded instantly with a hint and a full step-by-step solution. Progress is saved in this browser only.
- Surprisal: What Information Should Mean — 12 questions
- From Surprisal to Entropy: The Two Analytic Tools — 11 questions
- What the Measures Are For, and What They Are Not — 11 questions
- Definition of Entropy — 11 questions
- Properties of Entropy — 11 questions
- Calculating Entropy — 11 questions
- Joint Entropy — 11 questions
- Joint Entropy Against Its Marginals — 11 questions
- The Chain Rule — 11 questions
- Definition of Conditional Entropy — 11 questions
- Conditioning Reduces Entropy, and Fano's Inequality — 11 questions
- Chain Rules and the Algebra of Conditioning — 11 questions