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1.1 - Introduction

1.2 - Probability in the Real World

1.3 - Why Probability Matters

1.4 - Probability in Action

1.5 - The Nuances of Probability

1.6 - Conclusion

Exercise : What is the Difference Between Theoretical and Experimental Probability?

2.1 - Understanding Probability

2.2 - Basic Probability Terms

2.3 - Probability Axioms

2.4 - Addition and Multiplication Rules in Probability

2.5 - Conditional Probability

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Exercise : Basic Concepts of Probability

Exercise : General Probability Rules

Exercise : Laplace Definition

3.1 - Bayes Theorem

3.2 - Random Variables in Probability

3.3 - Probability Distributions

3.4 - Joint Probability and Independence

3.5 - Conditional Probability Continued

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Exercise : Random Variables

4.1 - Covariance and Correlation

4.2 - Law of Large Numbers and Central Limit Thoerem

4.3 - Bayesian Inference

4.4 - Markov Chains

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Exercise : Law of Large Number

Exercise : The Central Limit Theorem

5.1 - The Probability Scale

5.2 - Probability in Descriptive and Inferential Statistics

5.3 - Examples of Probability in Data Analysis

5.4 - Why Do We Need Probability in Data Analysis?

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