## Introduction

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.

<a href="//www.youtube.com/watch?v=wXTVenlgpvU" rel="nofollow" target="_blank"><img src="//img.youtube.com/vi/wXTVenlgpvU/0.jpg" alt="0" title="How To Choose The Correct Channel Type For Your Video Content " /></a>

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.

What you'll learn:

• 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

## Meet The Faculty

### Benedict Gross

Leverett Professor of Mathematics, Emeritus, Harvard University

Benedict H. (Dick) Gross is the George Vasmer Leverett Professor of Mathematics, Emeritus at Harvard University. Dick received his A.B. and Ph.D. degrees from Harvard, and taught at Princeton and Brown before joining the Harvard faculty in 1985. He has served as chair of the Department of Mathematics, and as the Dean of Harvard College. Among his awards and honors are the Cole Prize from the American Mathematical Society, and a MacArthur Fellowship. He is a member of the National Academy of Sciences and the American Philosophical Society.

As an undergraduate at Harvard, Dick concentrated in mathematics. He was a recipient of a Sheldon fellowship after graduating, which he used to study music in Africa and Asia, and a Marshall Scholarship, which he took at Oxford University. He is now retired and living in the San Diego area, where he holds a part-time position in the mathematics department of UCSD.

### Joseph Harris

Higgins Professor of Mathematics, Harvard University

Joe Harris is the Higgins Professor of Mathematics at Harvard University. He received the Ph.D. from Harvard in 1977, and was on the faculty at M.I.T. and Brown University before returning to Harvard in 1988. Together with Professor Gross, he developed the courses Magic of Numbers and Fat Chance, intended to introduce non-mathematically inclined students to number theory and probability. Harris' research is in the field of Algebraic Geometry, the study of the geometry of solutions to polynomial equations. He is a member of the National Academy of Science.

### Emily Riehl

Assistant Professor, Department of Mathematics, Johns Hopkins University

Emily Riehl is an assistant professor in the department of mathematics at Johns Hopkins University. She earned her AB from Harvard College in 2006, a Masters of Advanced Study in Mathematics from Cambridge University in 2007, and her PhD from the University of Chicago in 2011. From 2011-2015, she was a Benjamin Peirce and NSF Postdoctoral Fellow in the department of mathematics at Harvard University. Her research speciality is category theory, the "mathematics of mathematics," which studies very general paradigms of mathematical proof that apply simultaneously in many different contexts. In particular, she has worked to develop the foundational theory of infinite-dimensional categories, which are inhabited by objects whose transformations may be related by "homotopies," which themselves may be related by "higher homotopies," and so on ad infinitum. In addition to roughly two dozen research papers, mostly written in collaboration, she is the author of two advanced mathematics textbooks Categorical Homotopy Theory (Cambridge University Press 2014) and Categorical Homotopy Theory (Dover 2016) and can be found on YouTube giving lectures on the stable marriage problem.

Data Science