Probability and Statistics I: A Gentle Introduction to Probability
Offered By: Georgia Institute of Technology via edX
Course Description
Overview
This course provides an introduction to basic probability concepts. Our emphasis is on applications in science and engineering, with the goal of enhancing modeling and analysis skills for a variety of real-world problems.
In order to make the course completely self-contained (and to bring back long-lost memories), we’ll start off with Bootcamp lessons to review concepts from set theory and calculus. We’ll then discuss the probability axioms that serve as the basis for all of our subsequent work – what makes probability tick? That discussion will give us the tools to study elementary probability counting rules, including permutations and combinations. We’ll use these rules to work on various cool applications, including poker probability calculations and baseball line-ups!
The next venues on our tour are the concepts of independence and conditional probability, which allow us to see how the probabilities of different events are related to each other, and how new information can be used to update probabilities. The course culminates in a discussion of Bayes Rule and its various interesting consequences related to probability updates.
Syllabus
“FCPS” refers to the free text, A First Course in Probability and Statistics: free access is provided via a PDF file or as a book
Module 1: Course Introduction + Bootcamps
• Lesson 1: Introduction to Probability and Statistics (FCPS §1.1)
• Lesson 2 [OPTIONAL]: The Joy of Sets Bootcamp (FCPS §1.2.1)
• Lesson 3 [OPTIONAL]: Calculus Bootcamp: Introduction + Derivatives (FCPS §1.2.2)
• Lesson 4 [OPTIONAL]: Calculus Bootcamp: Integration and Beyond (FCPS §1.2.2)
Module 2: Getting Started with Probability
• Lesson 1: Experiments, Sample Spaces, and Events (FCPS §§1.3.1−1.3.2)
• Lesson 2: What is Probability? (FCPS §1.3.3)
• Lesson 3: Basic Probability Results (FCPS §1.3.3)
• Lesson 4: Finite Sample Spaces (FCPS §1.4)
• Lesson 5: Counting Techniques: Baby Examples (FCPS §1.5.1)
• Lesson 6: Counting Techniques: Permutations (FCPS §1.5.2)
• Lesson 7: Counting Techniques: Combinations (FCPS §1.5.3)
• Lesson 8: Hypergeometric, Binomial, and Multinomial Problems (FCPS §§1.6.1−1.6.3)
• Lesson 9: Permutations vs. Combinations (FCPS §1.6.4)
• Lesson 10: The Birthday Problem (FCPS §1.6.5)
• Lesson 11: The Envelope Problem (FCPS §1.6.6)
• Lesson 12: Poker Problems (FCPS §1.6.7)
• Lesson 13: Conditional Probability (FCPS §1.7.1)
• Lesson 14: Independence Day (FCPS §1.7.2)
• Lesson 15: Partitions and the Law of Total Probability (FCPS §1.8)
• Lesson 16: Bayes Theorem (FCPS §1.8)
Taught by
David Goldsman
Tags
Related Courses
Advanced Machine LearningThe Open University via FutureLearn On-Ramp to AP* Calculus
Weston High School via edX Preparing for the AP* Calculus AB and BC Exams
University of Houston System via Coursera Calculus: Single Variable Part 4 - Applications
University of Pennsylvania via Coursera Applied Calculus with Python
Johns Hopkins University via Coursera