### FC1x: Fat Chance: Probability from the Ground Up

#### Course Instructors

• Benedict Gross; Leverett Professor of Mathematics, Emeritus; Harvard University
• Joseph Harris; Higgins Professor of Mathematics; Harvard University
• Emily Riehl; Assistant Professor, Department of Mathematics; Johns Hopkins University

#### Course Description

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.

#### What You'll Learn in the Course

In this course you will:

1. Gain an increased appreciation for, and reduced fear of, basic probability and statistics
2. Learn how to solve combinatorial counting problems
3. Learn how to solve problems using basic and advanced probability
4. Develop an introductory understanding of the normal distribution and its many statistical applications
5. Recognize common fallacies in probability, as well as some of the ways in which statistics are abused or simply misunderstood

#### Key Dates

This self-paced course opened on April 24, 2018 and closes on October 23, 2018. The only due date for assessments is the final course end date.

To pass the course, you must earn a grade of 60% or higher.

Each module in the course consists of the following exercises:

• NOTE: All practice problems include OPTIONAL explanation videos called Office Hours. Office Hour videos walk you through practice problems in a step-by-step manner.

The grading system will automatically drop your lowest practice set score and your lowest evaluation set score. These drops appear as an "x" in your Progress chart.

#### Course Outline

This course is cumulative, meaning each module builds and expands upon the concepts covered in the previous module. We recommend that you follow the prescribed sequence.

The modules:

• Part I: Counting
• 1 Basic Counting
• Part II: Probability
• 3 Basic Probability
• 4 Expected Value
• 5 Conditional Probability
• 6 Bernoulli Trials
• Part III: Statistics
• 7 The Normal Distribution

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#### Research Statement

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