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Joseph Blitzstein

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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.

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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

- 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

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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

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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 Introduction to Probability to your list so you can find it easily later:

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"

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

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- 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

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Familiarize yourself with core probability concepts

View
Introduction to Probability, Second Edition...
on Amazon

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- 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

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Engage with peers to clarify concepts and reinforce understanding

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- 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

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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

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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

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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

Learners who complete Introduction to Probability will develop knowledge and skills
that may be useful to these careers:

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

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 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

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 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 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 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 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 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 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 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 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 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

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

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:
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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.

For more information about how these books relate to this course, visit:
**
OpenCourser.com/course/rz4zmu/introduction
**

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