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# HarvardX Data Science - Probability (PH125.3x)

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## Course Description

Gain important foundational knowledge in probability theory, essential for data scientist, as you learn key concepts through a motivating case study on the financial crisis of 2007-08. Find the complete course on edx.org here.
1. 1

### Introduction to Discrete Probability

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In this chapter, you will learn about the fundamentals of discrete probability through looking at examples of sampling from an urn with and without replacement.

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Exercise 1. Probability of cyan - generalized
100 xp
Exercise 2. Probability of not cyan - generalized
100 xp
Exercise 3. Sampling without replacement - generalized
100 xp
Exercise 4. Sampling with replacement - generalized
100 xp
End of Assessment: Introduction to Discrete Probability
50 xp
2. 2

### Independence and Multiplication Rule

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In this chapter, you will learn about independence, conditional probability, and the multiplication rule through examples involving draws from an urn, rolls of a die, and sports series wins.

3. 3

### The Addition Rule

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In this chapter, you will learn about the addition rule and the Monty Hall problem.

4. 4

### Continuous Probability

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In this chapter, you will learn about continuous probability through the use of examples involving the distribution of heights and IQ scores.

5. 5

### Random Variables and Sampling Models

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In this chapter, you will learn about random variables and sampling models exploring an example looking at various aspects of the game of chance American Roulette.

6. 6

### The Central Limit Theorem

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In this chapter, you will learn about the Central Limit Theorem and compare results from Monte Carlo simulations to those obtained using the Central Limit Theorem for games of chance.

7. 7

### The Big Short

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In this chapter, you will learn about interest rates and the big short.

Weston Stearns

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