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Course Curriculum

The Basics of Probability
1.1 Complements 00:00:00
1.2 Computing Expected Values 00:00:00
1.3 The Probability Frequency Distribution 00:00:00
1.4 What is the probability formula 00:00:00
2 Combinatorics
2.1 A Summary of Combinatorics 00:00:00
2.2 Combinations with Separate Sample Spaces 00:00:00
2.3 Combinatorics Practical Example 00:00:00
2.4 Computing Combinations 00:00:00
2.5 Computing Permutations 00:00:00
2.6 Computing Variations with Repetition 00:00:00
2.7 Computing Variations without Repetition 00:00:00
2.8 Fundamentals of Combinatorics 00:00:00
2.9 Solving Factorials 00:00:00
2.10 Symmetry of Combinations 00:00:00
2.11Winning the Lottery 00:00:00
Bayesian Inference
3.1 Additive Law 00:00:00
3.2 Bayes Rule 00:00:00
3.3 Bayesian Practical Example 00:00:00
3.4 Conditional Probability 00:00:00
3.5 Dependent and Independent Events 00:00:00
3.6 Law of Total Probability 00:00:00
3.7 Multiplication Rule 00:00:00
3.8 Mutually Exclusive Sets 00:00:00
3.9 Sets and Events 00:00:00
3.10 The Different Ways Events Can Interact 00:00:00
3.11 The Intersection of Two Sets 00:00:00
3.12 The Union of Two Sets 00:00:00
Probability Distributions
4.1 An overview of distributions 00:00:00
4.2 Bernoulli Distributions 00:00:00
4.3 Binomial Distributions 00:00:00
4.4 Chi Squared Distributions 00:00:00
4.5 Continuous Distributions 00:00:00
4.6 Discrete Distributions 00:00:00
4.7 Discrete Uniform Distributions 00:00:00
4.8 Exponential Distributions 00:00:00
4.9 Logistic Distributions 00:00:00
4.10 Normal Distributions 00:00:00
4.11 Poisson Distributions 00:00:00
4.12 Probability Distributions A Practical Example 00:00:00
4.13 Standardizing Normal Distributions 00:00:00
4.14 Students’ T Distributions 00:00:00
4.15 Types of Distributions 00:00:00
Probability In Other Fields
5.1 Probability in Data Science 00:00:00
5.2 Probability in Finance 00:00:00
5.3 Probability in Statistics 00:00:00

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