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Joseph Blitzstein
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.
Read more
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.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/rz4zmu/introduction
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What's inside
Learning objectives
- 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
- 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
Syllabus
Unit 0: Introduction, Course Orientation, and FAQ
Unit 1: Probability, Counting, and Story Proofs
Unit 2: Conditional Probability and Bayes' Rule
Read more
Syllabus
Unit 0: Introduction, Course Orientation, and FAQ
Unit 1: Probability, Counting, and Story Proofs
Unit 2: Conditional Probability and Bayes' Rule
Read more
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
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores probability and statistics in a practical way, providing real-world examples from fields like medicine and sports
Taught by Joseph Blitzstein, a recognized expert in probability and data science
Develops a strong foundation in probability for further study in statistical inference and other related fields
Suitable for beginners who want to build a solid foundation in probability and statistics
May require additional knowledge in mathematics, particularly calculus, for some sections
The course does not cover advanced topics in probability and statistics
Save this course
Save Introduction to Probability to your list so you can find it easily later:
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Save
Reviews summary
Excellent introduction
According to students, Introduction to Probability makes complex topics, easy to understand. This well-written course, uses engaging graphics that solidifies complex concepts.
Graphics enhance learning experience.
"Very exciting I have always wanted to further my skills and this course has done just that opening the door for further learning"
Course content is well explained.
"It was well written good use of graphics to demonstrate"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Probability with these
activities:
Follow Khan Academy's 'Probability' playlist
Show steps
Build a strong foundation in probability
Browse courses on
Conditional Probability
Show steps
-
Create a Khan Academy account
-
Locate the 'Probability' playlist under 'Math'
-
Watch all the videos in the playlist
-
Complete the practice exercises and quizzes
Review 'Introduction to Probability' by Blitzstein
Show steps
Familiarize yourself with core probability concepts
View
Introduction to Probability, Second Edition...
on Amazon
Show steps
-
Read the first three chapters of the book
-
Annotate and summarize the main concepts covered
-
Complete the end-of-chapter exercises
Form a study group to discuss course material
Show steps
Engage with peers to clarify concepts and reinforce understanding
Show steps
-
Identify a group of classmates with similar interests
-
Schedule regular meetings
-
Discuss the course material, share insights, and work through problems together
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve probability problems from Brilliant.org
Show steps
Reinforce understanding of probability concepts through practice
Browse courses on
Probability Distributions
Show steps
-
Sign up for a Brilliant.org account
-
Navigate to the 'Probability' section
-
Complete at least 10 problems in each subsection
-
Review your solutions and identify areas for improvement
Develop a cheat sheet on probability distributions
Show steps
Summarize key concepts to enhance understanding and retention
Browse courses on
Probability Distributions
Show steps
-
Identify the most important probability distributions covered in the course
-
Gather information about each distribution (e.g., formula, parameters, properties)
-
Create a visually appealing cheat sheet
-
Review the cheat sheet regularly
Tutor other students in probability
Show steps
Deepen understanding by explaining concepts to others
Browse courses on
Probability
Show steps
-
Identify students who are struggling with the material
-
Offer your assistance and schedule tutoring sessions
-
Review the course concepts and work through problems together
-
Provide feedback and encouragement
Participate in the 'Chance' magazine's student essay contest
Show steps
Test your understanding and communication skills
Show steps
-
Read the contest guidelines and submission requirements
-
Brainstorm and develop a topic
-
Research and write a compelling essay
-
Proofread and edit your essay carefully
Follow Khan Academy's 'Probability' playlist
Show steps
Build a strong foundation in probability
Browse courses on
Conditional Probability
Show steps
Show steps
Show steps
- Create a Khan Academy account
- Locate the 'Probability' playlist under 'Math'
- Watch all the videos in the playlist
- Complete the practice exercises and quizzes
Review 'Introduction to Probability' by Blitzstein
Show steps
Familiarize yourself with core probability concepts
View
Introduction to Probability, Second Edition...
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters of the book
- Annotate and summarize the main concepts covered
- Complete the end-of-chapter exercises
Form a study group to discuss course material
Show steps
Engage with peers to clarify concepts and reinforce understanding
Show steps
Show steps
Show steps
- Identify a group of classmates with similar interests
- Schedule regular meetings
- Discuss the course material, share insights, and work through problems together
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve probability problems from Brilliant.org
Show steps
Reinforce understanding of probability concepts through practice
Browse courses on
Probability Distributions
Show steps
Show steps
Show steps
- Sign up for a Brilliant.org account
- Navigate to the 'Probability' section
- Complete at least 10 problems in each subsection
- Review your solutions and identify areas for improvement
Develop a cheat sheet on probability distributions
Show steps
Summarize key concepts to enhance understanding and retention
Browse courses on
Probability Distributions
Show steps
Show steps
Show steps
- Identify the most important probability distributions covered in the course
- Gather information about each distribution (e.g., formula, parameters, properties)
- Create a visually appealing cheat sheet
- Review the cheat sheet regularly
Tutor other students in probability
Show steps
Deepen understanding by explaining concepts to others
Browse courses on
Probability
Show steps
Show steps
Show steps
- Identify students who are struggling with the material
- Offer your assistance and schedule tutoring sessions
- Review the course concepts and work through problems together
- Provide feedback and encouragement
Participate in the 'Chance' magazine's student essay contest
Show steps
Test your understanding and communication skills
Show steps
Show steps
Show steps
- Read the contest guidelines and submission requirements
- Brainstorm and develop a topic
- Research and write a compelling essay
- Proofread and edit your essay carefully
Career center
Learners who complete Introduction to Probability will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist is responsible for collecting, cleaning, and analyzing data. They build machine learning models, identify trends and patterns, and help businesses make informed decisions. This course in Introduction to Probability is a great starting point for those looking to get into the field of data science. It provides a solid foundation in the fundamentals of probability, which is essential for understanding data and making accurate predictions.
Statistician
Statistician
Statisticians collect, analyze, interpret, and present data. They work in a variety of industries, including healthcare, finance, and marketing. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a statistician. The course covers topics such as probability distributions, hypothesis testing, and regression analysis.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts, also known as Quants, use mathematical and statistical models to analyze financial data and make investment decisions. They work for hedge funds, investment banks, and other financial institutions. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Quant. The course covers topics such as probability distributions, stochastic processes, and financial modeling.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They work in the insurance industry, helping to set premiums and design insurance policies. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as an Actuary. The course covers topics such as probability distributions, risk assessment, and financial modeling.
Risk Manager
Risk Manager
Risk Managers identify, assess, and manage risks. They work in a variety of industries, including finance, healthcare, and insurance. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Risk Manager. The course covers topics such as probability distributions, risk assessment, and decision making under uncertainty.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Software Engineer. The course covers topics such as probability distributions, algorithms, and data structures.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data. They work in a variety of industries, including healthcare, finance, and marketing. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Data Analyst. The course covers topics such as probability distributions, hypothesis testing, and regression analysis.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. They work for investment banks, hedge funds, and other financial institutions. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Financial Analyst. The course covers topics such as probability distributions, risk assessment, and financial modeling.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to improve the efficiency of business operations. They work in a variety of industries, including manufacturing, transportation, and healthcare. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as an Operations Research Analyst. The course covers topics such as probability distributions, optimization, and simulation.
Business Analyst
Business Analyst
Business Analysts help businesses make informed decisions by analyzing data and identifying trends. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Business Analyst. The course covers topics such as probability distributions, hypothesis testing, and regression analysis.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. They work for a variety of organizations, including marketing agencies, product development firms, and consulting companies. This course in Introduction to Probability provides a solid foundation in the fundamentals of probability, which is essential for a successful career as a Market Researcher. The course covers topics such as probability distributions, hypothesis testing, and regression analysis.
Project Manager
Project Manager
Project Managers are responsible for planning, executing, and closing projects. They work in a variety of industries, including construction, IT, and healthcare. This course in Introduction to Probability may be useful for those who want to get into project management. The course covers topics such as probability distributions, risk assessment, and decision making under uncertainty, which can be helpful for managing projects and making data-driven decisions.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They work in a variety of industries, including technology, consumer goods, and healthcare. This course in Introduction to Probability may be useful for those who want to get into product management. The course covers topics such as probability distributions, hypothesis testing, and regression analysis, which can be helpful for understanding customer behavior and making data-driven decisions.
Consultant
Consultant
Consultants provide advice to businesses and organizations on a variety of topics. This course in Introduction to Probability may be useful for those who want to get into consulting. The course covers topics such as probability distributions, hypothesis testing, and regression analysis, which can be helpful for analyzing data and making recommendations.
Teacher
Teacher
Teachers educate students at all levels, from elementary school to college. This course in Introduction to Probability may be useful for those who want to get into teaching. The course covers topics such as probability distributions, hypothesis testing, and regression analysis, which can be helpful for understanding student learning and making data-driven decisions.
For more career information including salaries, visit:
OpenCourser.com/course/rz4zmu/introduction
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Probability.
Is the official textbook for the course and provides a detailed and rigorous introduction to probability. It covers a wide range of topics, from basic concepts to advanced techniques.
Provides a comprehensive introduction to statistical inference, with a focus on the development of statistical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Save
Provides a comprehensive overview of statistical inference, with a focus on the development of statistical models. It is written in a clear and concise style and is suitable for students with a strong background in mathematics.
Save
Provides a comprehensive introduction to probability theory, with a focus on the development of mathematical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to real analysis and probability theory, with a focus on the development of mathematical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to measure theory and probability theory, with a focus on the development of mathematical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to probability theory and its applications, with a focus on the development of mathematical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to probability and measure theory, with a focus on the development of mathematical models. It is written in a rigorous and mathematical style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to Monte Carlo statistical methods, with a focus on applications in science and engineering. It is written in a clear and concise style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to stochastic processes, with a focus on applications in science and engineering. It is written in a clear and concise style and is suitable for students with a strong background in mathematics.
Provides a comprehensive introduction to probability and random processes, with a focus on applications in science and engineering. It is written in a clear and concise style and is suitable for students with a strong background in mathematics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rz4zmu/introduction
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Effort
5 to 10 hours per week for 10 weeks
Level
Intermediate
Via
edX
Institution
Harvard University
Instructor
Joseph Blitzstein
Language
English
Transcripts
Español
Français
Português
Deutsch
中文
العربية
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Türkçe
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Good to know
Explores probability and statistics in a practical way, providing real-world examples from fields like medicine and sports
Taught by Joseph Blitzstein, a recognized expert in probability and data science
Develops a strong foundation in probability for further study in statistical inference and other related fields
Suitable for beginners who want to build a solid foundation in probability and statistics
May require additional knowledge in mathematics, particularly calculus, for some sections
The course does not cover advanced topics in probability and statistics
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