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HarvardX: Introduction to Probability

4.4 stars
40 ratings

Learn probability, an essential language and set of tools for understanding data, randomness, and uncertainty.

10 weeks
5–10 hours per week
Self-paced
Progress at your own speed
Free
Optional upgrade available

There is one session available:

191,006 already enrolled! After a course session ends, it will be archivedOpens in a new tab.
Starts Nov 5

About this course

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Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.

With examples ranging from medical testing to sports prediction, you will gain a strong foundation for the study of statistical inference, stochastic processes, randomized algorithms, and other subjects where probability is needed.

At a glance

  • Institution: HarvardX
  • Subject: Data Analysis & Statistics
  • Level: Intermediate
  • Prerequisites:

    Familiarity with U.S. high school level algebra concepts; Single-variable calculus: familiarity with matrices. derivatives and integrals.

    Not all units require Calculus, the underlying concepts can be learned concurrently with a Calculus course or on your own for self-directed learners.

    Units 1-3 require no calculus or matrices; Units 4-6 require some calculus, no matrices; Unit 7 requires matrices, no calculus.

    Previous probability or statistics background not required.

  • Language: English
  • Video Transcripts: اَلْعَرَبِيَّةُ, Deutsch, Español, Français, हिन्दी, Bahasa Indonesia, Português, Kiswahili, తెలుగు, Türkçe, 中文
  • Associated skills:Probability, Medical Testing, Economics, Statistical Inference, Forecasting, Data Science, Finance, Stochastic Process, Engineering Economics, Prediction, Algorithms, Statistics

What you'll learn

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  • How to think about uncertainty and randomness
  • How to make good predictions
  • The story approach to understanding random variables
  • Common probability distributions used in statistics and data science
  • Methods for finding the expected value of a random quantity
  • How to use conditional probability to approach complicated problems
  • Unit 0: Introduction, Course Orientation, and FAQ
  • Unit 1: Probability, Counting, and Story Proofs
  • Unit 2: Conditional Probability and Bayes' Rule
  • Unit 3: Discrete Random Variables
  • Unit 4: Continuous Random Variables
  • Unit 5: Averages, Law of Large Numbers, and Central Limit Theorem
  • Unit 6: Joint Distributions and Conditional Expectation
  • Unit 7: Markov Chains

More about this course

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HarvardX Honor Code
HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.

HarvardX Nondiscrimination/Anti-Harassment Statement
Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact harvardx@harvard.edu and/or report your experience through the edX contact form.

HarvardX Research Statement
HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.

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