The Science of Data
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    • Introduction
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    • Counting
      • Basic Principles of Counting
      • Binomial Probability
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    • Conditional Probability
      • Definition
      • Bayes' Theorem
      • Independence
    • Discrete Random Variables
      • Discrete Random Variables
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      • Conditioning
      • Discrete Uniform Distribution
      • Bernoulli Random Variables
      • Binomial Distribution
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      • Negative Binomial Distribution
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    • Continuous Random Variables
      • Continuous Random Variables
      • Multiple Random Variables
      • Conditioning
      • Bayes' Rule
      • Continuous Uniform Distribution
      • Exponential Distribution
      • Gamma Distribution
      • The Gaussian Distribution
    • Further Topics
      • Derived Distributions
      • Covariance and Correlation
      • Revisiting Conditioning
    • Bayesian Inference
      • The Bayesian Inference Framework
      • The Unknown Bias of a Coin
      • Linear Models with Normal Noise
      • LLMS Estimation
    • Limit Theorems
      • The Weak Law of Large Numbers
      • The Central Limit Theorem
    • Stochastic Processes
      • The Bernoulli Process
      • Merging of Bernoulli Processes
      • Splitting of Bernoulli Process
      • The Poisson Process
      • Merging of Poisson Processes
      • Splitting of a Poisson Process
    • Markov Processes
      • Markov Processes I
      • Markov Processes II

    Bayes' Rule