Interactive Course

HarvardX Data Science - Probability (PH125.3x)

  • 0 hours
  • 0 Videos
  • 52 Exercises
  • 14,138 Participants
  • 4,650 XP

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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

    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.

  2. 3

    The Addition Rule

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

  3. 5

    Random Variables and Sampling Models

    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.

  4. 7

    The Big Short

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

  5. 2

    Independence and Multiplication Rule

    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.

  6. 4

    Continuous Probability

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

  7. 6

    The Central Limit Theorem

    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.

  1. 1

    Introduction to Discrete Probability

    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.

  2. 2

    Independence and Multiplication Rule

    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

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

  4. 4

    Continuous Probability

    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

    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

    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

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

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