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# Fat Chance: Probability from the Ground Up

### Overview

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.

### Syllabus

1 Basic Counting

• 1.1 Counting Numbers
• 1.2 Large Numbers
• 1.3 The Multiplication Principle
• 1.4 More on the Multiplication Principle and Factorials
• 1.5 The Subtraction Principle

• 2.1 Counting Collections
• 2.2 Binomial Coefficients
• 2.3 Applications of Collections
• 2.4 Multinomials
• 2.5 Collections with Repetition

3 Basic Probability

• 3.1 Flipping Coins
• 3.2 Rolling Dice
• 3.3 Playing Poker
• 3.4 Distributions of Bridge Hands

4 Expected Value

• 4.1 Expected Value: Chuck-A-Luck
• 4.2 Expected Value: Slot Machines
• 4.3 Strategizing

5 Conditional Probability

• 5.1 The Monty Hall Problem
• 5.2 Conditional Probability: Set-Up and Examples
• 5.3 Conditional Probability: Elections

6 Bernoulli Trials

• 6.1 Bernoulli Trials
• 6.2 The Gambler's Ruin

7 The Normal Distribution

• 7.1 Games
• 7.2 Games: Examples and Variance
• 7.3 Iterating Games
• 7.4 The Normal Distribution - Part 1
• 7.5 The Normal Distribution - Part 2

### Taught by

Benedict Gross, Joseph Harris and Emily Riehl

## Reviews

4.8 rating, based on 5 Class Central reviews

4.6 rating at edX based on 47 ratings

Start your review of Fat Chance: Probability from the Ground Up

• I loved this course - it was at exactly the level I needed. I particularly iiked the "office hours" feature : a video for each Practice Exercise, giving a clear step-by-step explanation of how the problem was approached and solved. I have a lot of trouble with math, especially stats, so this was very encouraging.
FMI see my blog post at https://sloopie72.wordpress.com/2018/05/30/fat-chance-counting-probability-mooc/
• My goal for talking this course was to understand the intuition behind probability and statistics. Although I had an introductory course a few decades ago, my emphasis was on memorization and manipulation of formulas. So, I found this course very heâ€¦
• Anonymous
I've had doezens of MOOCs so far, mainly from coursera to edX, and this is definitely one of the best MOOC I've ever encountered. The course materials are easy to understand, and the video lectures are vivid, attractive and really helps you understanding the concepts. There are a lot of examples to go with the concept illustrated. And there are videos explaning the practise which really helps me consolidate the knowledge.

All the three instructors are really good at their jobs, and they make math so much fun than I ever expected!

Absolutely love this course!!!
• Anonymous
If you're looking for a course that starts at the very basic concepts and builds up your intuition slowly, this one is for you. I found it very helpful. It's worth mentioning it is very well made.
• Anonymous
No word to say,it was just amazing,cool and mind blowing probability course ever!
I think each and every mathematics student should enroll in this course.
Thanks to edX and HX for bringing course like Fat Chance.

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