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Fat Chance

Probability from the Ground Up

Benedict Gross, Joseph Harris, and Emily Riehl

4.3

Based on 6 ratings

, see reviews

Benedict Gross, Joseph Harris, and Emily Riehl

Created specifically for those who are new to the study of probability, or for those who are seeking an approachable review of core concepts prior to enrolling in a college-level statistics course, Fat Chance prioritizes the development of a mathematical mode of thought over rote memorization of terms and formulae. Through highly visual lessons and guided practice, this course explores the quantitative reasoning behind probability and the cumulative nature of mathematics by tracing probability and statistics back to a foundation in the principles of counting.

In Modules 1 and 2, you will be introduced to basic counting skills that you will build upon throughout the course. In Module 3, you will apply those skills to simple problems in probability. In Modules 4 through 6, you will explore how those ideas and techniques can be adapted to answer a greater range of probability problems. Lastly, in Module 7, you will be introduced to statistics through the notion of expected value, variance, and the normal distribution. You will see how to use these ideas to approximate probabilities in situations where it is difficult to calculate their exact values.

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What's inside

Learning objectives

An increased appreciation for, and reduced fear of, basic probability and statistics
How to solve combinatorial counting problems
How to solve problems using basic and advanced probability

An introductory understanding of the normal distribution and its many statistical applications
An ability to recognize common fallacies in probability, as well as some of the ways in which statistics are abused or simply misunderstood

An increased appreciation for, and reduced fear of, basic probability and statistics
How to solve combinatorial counting problems
How to solve problems using basic and advanced probability
An introductory understanding of the normal distribution and its many statistical applications
An ability to recognize common fallacies in probability, as well as some of the ways in which statistics are abused or simply misunderstood

Syllabus

1 Basic Counting

1.1 Counting Numbers

1.2 Large Numbers

1.3 The Multiplication Principle

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores probability and statistics through the principles of counting, making the concepts easy to grasp

Suitable for beginners with little to no prior knowledge in probability and statistics

Provides a strong foundation for students pursuing further studies in statistics or related fields

Covers a wide range of topics, including basic counting, advanced counting, basic probability, expected value, conditional probability, Bernoulli trials, and the normal distribution

Taught by instructors with expertise in mathematics and statistics

Concepts are explained clearly and concisely, making the course accessible to a broad audience

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Create your own learning path. Save this course to your list so you can find it easily later.

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Reviews summary

Probability from the ground up

According to learners, Fat Chance provides a strong foundation (positive) in probability and statistics, starting from basic counting principles. Many found the explanations clear and easy to follow (positive), especially praising the visual lessons (positive) and the instructor's ability to break down complex topics. Students appreciate how the course builds concepts progressively (positive), making it suitable for those new to the subject or needing a review. While largely positive, a few noted that later modules, particularly on the normal distribution, could benefit from more depth or examples (warning). Overall, it successfully helps learners reduce fear (positive) and gain a working understanding of probability.

Great starting point for new learners.

"As someone with zero background in probability, this course was the perfect starting point."

"It really helps someone who is intimidated by math or stats to feel comfortable with the material."

"This course is exactly what I needed to get comfortable with the basics before taking a college statistics class."

Lessons are engaging and visually helpful.

"The visual aids used in the lectures were incredibly helpful in understanding the concepts."

"I found the course very engaging, the way it was presented kept my attention."

"The use of examples and visuals made the abstract ideas much more concrete and understandable."

Successfully builds from basics (counting).

"Starting with counting was a brilliant approach. It laid a very solid foundation for everything else."

"The way this course builds probability from the ground up using counting principles is excellent."

"I felt I really understood the core concepts because the course started with the absolute basics and built up gradually."

"This course gave me a great understanding of the fundamentals needed for more advanced stats courses."

Instructor excels at making concepts clear.

"The instructor has an incredible ability to explain complex probability concepts in a way that is both simple and intuitive."

"His explanations are extremely clear and he builds everything from the ground up, just as the course title suggests."

"I really appreciated the way the concepts were explained; it made learning probability feel much less intimidating than expected."

"The instructor's approach is fantastic, breaking down each topic step-by-step making it really easy to follow along."

Some find later topics less detailed.

"While the first half was excellent, the later modules, especially on the normal distribution, felt a bit rushed and less in-depth compared to earlier parts."

"I wish there were more examples and a bit more detail provided in the section covering the normal distribution."

"The introductory part was fantastic, but as the course progressed to more complex topics, I felt the explanations were sometimes too brief."

"Could benefit from slightly more comprehensive coverage of the advanced concepts introduced towards the end."

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 Fat Chance: Probability from the Ground Up with these activities:

Review Set Theory Concepts

Show steps

Review the basics of set theory, which provides the foundation for probability concepts like events and outcomes.

Browse courses on Set Theory

Show steps

Go over definitions of sets, subsets, and operations
Review properties and laws of set theory

Revisit Counting Principles

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Review the multiplication, subtraction, and counting principles to build a strong foundation for topics covered later in the course.

Browse courses on Counting Principles

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Review multiplication principle and counting factorials
Review subtraction principle

Connect with a Probability Expert

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Reach out to individuals in your network or online communities to find a mentor who can provide guidance, support, and insights into probability concepts.

Browse courses on Probability

Show steps

Identify potential mentors through professional organizations or social media
Reach out and express your interest in connecting
Establish regular communication and seek their guidance on specific topics

Six other activities

Expand to see all activities and additional details

Show all nine activities

Create a Collection of Probability Resources

Show steps

Gather and organize a collection of valuable resources such as articles, videos, and simulations to supplement your learning and provide additional perspectives on probability concepts.

Browse courses on Probability

Show steps

Identify and gather relevant resources
Organize the resources into categories or topics
Create a central repository for easy access

Form a Study Group for Probability

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Join or form a study group to collaborate with peers, discuss concepts, and work through problems together to enhance your understanding.

Browse courses on Probability

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Find or create a study group with compatible peers
Establish regular meeting times and a study schedule
Take turns presenting concepts, solving problems, and facilitating discussions

Probability Calculations Practice

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Solve a variety of probability problems to develop fluency and strengthen your problem-solving abilities.

Browse courses on Probability

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Find practice problems from textbooks or online resources
Attempt to solve the problems independently
Check your solutions and identify areas where you need improvement

Solve Probability Puzzles

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Practice solving challenging probability puzzles to sharpen your problem-solving skills and deepen your understanding of probability concepts.

Browse courses on Probability

Show steps

Find online or textbook-based probability puzzles
Attempt to solve the puzzles using the concepts learned in the course
Review solutions and identify areas for improvement

Develop Visual Guide to Probability

Show steps

Create a visual guide that summarizes key probability concepts, helping you visualize and understand complex ideas.

Browse courses on Probability

Show steps

Research and gather information on probability concepts
Design a visual representation of each concept
Compile the visual representations into a coherent guide

Attend a Probability Workshop

Show steps

Participate in a workshop led by experts to gain hands-on experience with probability concepts and learn from industry professionals.

Browse courses on Probability

Show steps

Research and identify relevant workshops
Register and attend the workshop
Actively participate in discussions and exercises

Career center

Learners who complete Fat Chance: Probability from the Ground Up will develop knowledge and skills that may be useful to these careers:

Statistician

Statisticians collect, analyze, and interpret data. They use their knowledge of probability and statistics to draw conclusions about the world around us. This course can help statisticians build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in statistics to model the distribution of data.

See salaries and explore the career path for Statistician

Actuary

Actuaries analyze the financial consequences of risk and uncertainty. They use mathematical and statistical skills to determine the probability of future events and to assess their financial impact. Probability is a fundamental concept in actuarial work, and this course can help build a strong foundation in the subject. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in actuarial work to model the distribution of risks.

See salaries and explore the career path for Actuary

Financial Analyst

Financial analysts evaluate the financial performance of companies and make recommendations for investment decisions. They use their knowledge of probability and statistics to assess the risk and return of different investments. This course can help financial analysts build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in financial analysis to model the distribution of returns.

See salaries and explore the career path for Financial Analyst

Insurance Agent

Insurance agents sell insurance policies to individuals and businesses. They use their knowledge of probability and statistics to assess the risk of different events and to determine the appropriate amount of coverage. This course can help insurance agents build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in insurance to model the distribution of claims.

See salaries and explore the career path for Insurance Agent

Investment Banker

Investment bankers help companies raise capital by selling stocks and bonds. They use their knowledge of probability and statistics to assess the risk and return of different investments. This course can help investment bankers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in investment banking to model the distribution of returns.

See salaries and explore the career path for Investment Banker

Market Researcher

Market researchers conduct surveys and collect data to understand consumer behavior. They use their knowledge of probability and statistics to design and analyze surveys and to draw conclusions about consumer behavior. This course can help market researchers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in marketing research to model the distribution of consumer behavior.

See salaries and explore the career path for Market Researcher

Operations Research Analyst

Operations research analysts use mathematical and statistical techniques to improve the efficiency of business operations. They use their knowledge of probability and statistics to model business processes and to make recommendations for improvement. This course can help operations research analysts build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in operations research to model the distribution of business processes.

See salaries and explore the career path for Operations Research Analyst

Risk Analyst

Risk analysts identify and assess the risks that organizations face. They use their knowledge of probability and statistics to quantify the likelihood and impact of different risks. This course can help risk analysts build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in risk analysis to model the distribution of risks.

See salaries and explore the career path for Risk Analyst

Quantitative Analyst

Quantitative analysts use mathematical and statistical techniques to analyze financial data and make investment decisions. They use their knowledge of probability and statistics to assess the risk and return of different investments. This course can help quantitative analysts build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in quantitative analysis to model the distribution of returns.

See salaries and explore the career path for Quantitative Analyst

Data Analyst

Data analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations for businesses and organizations. Probability and statistics are essential skills for data analysts, and this course can help build a strong foundation in these subjects. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in data analysis to model the distribution of data.

See salaries and explore the career path for Data Analyst

Underwriter

Underwriters assess the risk of insurance policies and determine the appropriate premiums. They use their knowledge of probability and statistics to assess the likelihood and impact of different risks. This course can help underwriters build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in underwriting to model the distribution of risks.

See salaries and explore the career path for Underwriter

Data Engineer

Data engineers design, build, and maintain data systems. They use their knowledge of probability and statistics to ensure that data systems are reliable and efficient. This course can help data engineers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in data engineering to model the distribution of data.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine learning engineers design and develop machine learning models. They use their knowledge of probability and statistics to train and evaluate machine learning models. This course can help machine learning engineers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in machine learning to model the distribution of data.

See salaries and explore the career path for Machine Learning Engineer

Teacher

Teachers develop and deliver lesson plans to students in a variety of settings. They use their knowledge of probability and statistics to teach students about the world around them. This course can help teachers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in education to model the distribution of student performance.

See salaries and explore the career path for Teacher

Software Engineer

Software engineers design, develop, and maintain software systems. They use their knowledge of probability and statistics to ensure that software systems are reliable and efficient. This course can help software engineers build a strong foundation in probability and statistics. The course covers basic probability concepts such as counting, expected value, and conditional probability. It also introduces the normal distribution, which is widely used in software engineering to model the distribution of data.

See salaries and explore the career path for Software Engineer

Reading list

We've selected 16 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 Fat Chance: Probability from the Ground Up.

Mathematical Statistics with Applications

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This introductory textbook covers a wide range of topics in mathematical statistics, including probability theory, statistical inference, and regression analysis. It provides a strong foundation for further studies in statistics and is recommended for learners who want to pursue a more rigorous approach to the subject.

Mathematical Statistics with Applications

Hardcover

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Mathematical Statistics with Applications

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Mathematical Statistics with Applications

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WebAssign Access Card for Mathematical Statistics...

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Mathematical Statistics with Applications

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Growth, Distribution and Effective Demand:...

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This widely-used textbook provides a comprehensive introduction to statistical methods for research. It covers a range of topics, from basic concepts to advanced statistical techniques, making it a valuable reference for learners who want to expand their statistical knowledge beyond the scope of this course.

Growth, Distribution and Effective Demand:...

Paperback

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Growth, Distribution and Effective Demand:...

Kindle Edition

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Probability Essentials

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This concise textbook provides a mathematically rigorous introduction to probability theory. It covers essential concepts such as measure theory, random variables, and conditional expectation, making it a valuable resource for learners who want to develop a strong theoretical foundation in probability.

Probability Essentials

Paperback

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Naked Statistics

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This accessible book demystifies statistics, making it approachable for readers with little or no mathematical background. It provides a practical guide to understanding and interpreting statistical information in everyday life.

Naked Statistics: Stripping the Dread from the Data

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NEW-Naked Statistics

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Naked Statistics: Stripping the Dread from the Data

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Bayesian Data Analysis, Third Edition

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This comprehensive textbook provides an introduction to Bayesian statistics, a powerful approach to statistical inference that is gaining increasing popularity. It offers a different perspective on probability and statistics, particularly relevant for learners interested in data analysis and machine learning.

Bayesian Data Analysis (Chapman & Hall/CRC Texts in...

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Introduction to Probability, Second Edition

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This textbook provides a comprehensive introduction to probability theory, covering topics such as counting, probability spaces, random variables, and statistical inference. It valuable resource for students who want to gain a strong foundation in probability.

Introduction to Probability, Second Edition...

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Introduction to Probability, Second Edition...

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Introduction to Stochastic Processes

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This textbook introduces the theory of stochastic processes, which are random processes that evolve over time. It covers topics such as Markov chains, Brownian motion, and martingales, providing learners with a foundation for understanding the probabilistic behavior of dynamic systems.

Introduction to Stochastic Processes (Chapman &...

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Introduction to Stochastic Processes (Chapman &...

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Probability & Statistics for Engineers & Scientists

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This textbook is designed for students in engineering and science who need a strong foundation in probability and statistics. It covers a wide range of topics, including probability distributions, hypothesis testing, and regression analysis.

Probability & Statistics for Engineers & Scientists

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Probability and Statistics for Engineers and...

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Probability & Statistics for Engineers & Scientists

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Probability & Statistics for Engineers & Scientists...

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Probability and Statistics for Engineers and...

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Probability & Statistics for Engineers & Scientists...

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Cautionary Tales in Designed Experiments

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Presents a fascinating history of the development of statistics, highlighting its role in shaping scientific discoveries. It provides a broader context for understanding the significance of probability and statistics in various fields.

Cautionary Tales in Designed Experiments

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Cautionary Tales in Designed Experiments

Kindle Edition

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All of Statistics

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This textbook provides a concise overview of statistical inference, covering topics such as point estimation, hypothesis testing, and Bayesian statistics. It valuable resource for students who want to gain a broad understanding of statistics.

All of Statistics: A Concise Course in Statistical...

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All of Nonparametric Statistics (Springer Texts in...

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All of statistics : A concise course in statistic...

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Elements of Information Theory

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This classic textbook on information theory provides a mathematical foundation for understanding the transmission and processing of information. It introduces concepts such as entropy, mutual information, and channel capacity, which are closely related to probability and statistics.

Elements of Information Theory 2nd Edition (Wiley...

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Elements of Information Theory

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The Book of Why

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Explores the concepts of causality and counterfactuals, providing insights into the relationship between probability and causation. It offers a unique perspective that complements the course's focus on probability.

The Book of Why: The New Science of Cause and Effect

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Data Science for Business

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Introduces the principles and practices of data science in a business context. It covers topics such as data collection, analysis, and visualization, providing learners with a practical understanding of how probability and statistics are used in real-world business applications.

Data Science for Business: What You Need to Know...

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Data Science for Business: What You Need to Know...

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The Elements of Statistical Learning

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This textbook classic introduction to statistical learning, covering topics such as supervised learning, unsupervised learning, and model selection. It valuable resource for students who want to learn about the latest advances in machine learning.

The Elements of Statistical Learning: Data Mining,...

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The Elements of Statistical Learning: Data Mining,...

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The Elements of Statistical Learning: Data Mining,...

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Fundamentals of Actuarial Mathematics

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Focuses on applying probability and statistics to financial problems. It covers topics such as risk analysis, portfolio optimization, and derivative pricing, providing learners with a practical understanding of how probability is used in the financial industry.

Fundamentals of Actuarial Mathematics (Wiley...

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Fundamentals of Actuarial Mathematics (Wiley...

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Fundamental Statistics for the Behavioral Sciences...

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This textbook provides a practical introduction to statistical methods for students in psychology. It covers a wide range of topics, including descriptive statistics, inferential statistics, and multivariate analysis.

Fundamental Statistics for the Behavioral Sciences...

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Fundamental Statistics for the Behavioral Sciences...

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Rating

4.3

Effort

3 to 5 hours per week for 7 weeks

Level

Introductory

Via

edX

Institution

Harvard University

Instructors

Benedict Gross

Joseph Harris

Emily Riehl

Language

English

Transcripts

English Español Français Português Deutsch 中文 العربية हिंदी Türkçe తెలుగు Bahasa Indonesia Kiswahili

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores probability and statistics through the principles of counting, making the concepts easy to grasp

Suitable for beginners with little to no prior knowledge in probability and statistics

Provides a strong foundation for students pursuing further studies in statistics or related fields

Covers a wide range of topics, including basic counting, advanced counting, basic probability, expected value, conditional probability, Bernoulli trials, and the normal distribution

Taught by instructors with expertise in mathematics and statistics

Concepts are explained clearly and concisely, making the course accessible to a broad audience

Fat Chance

Probability from the Ground Up

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Probability from the ground up

Activities

Career center

Reading list

Share

Similar courses

edX Buyer Protection & Guarantee

Free Audit Track Available

14-Day Full Refund Window

Verified Academic & Industry Partner