Probability Theory and Examples: A Guided Course With Intuition, Proofs, and Worked Problems for Self-Study

Daniel Hofstadter

Master probability theory and applied statistics on the go with this patient, audio-optimized self-study guide. Transform your daily commute or focused study sessions into a conversational journey through the hidden laws of randomness. Designed...

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Opening Credits

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Chapter 1: Seeing the World Through Chance

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Chapter 2: Sample Spaces, Events, and the Rules of Probability

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Chapter 3: Counting and Combinatorics Made Intuitive

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Chapter 4: Conditional Probability, Independence, and Bayes Thinking

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Chapter 5: Discrete Random Variables and Their Distributions

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Chapter 6: Continuous Random Variables and Density Intuition

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Chapter 7: Expectation, Variance, and Useful Inequalities

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Chapter 8: Joint Distributions, Covariance, and Transformations

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Chapter 9: From Many Trials to Predictable Patterns: Laws of Large Numbers and the Central Limit Theorem

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Chapter 10: Modeling the Real World and Putting It All Together

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Closing Credits

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