Watch the following lectures on probability by the instructor. Then practice your knowledge using the Khan Academy links.
The instructor's exercises are available on this Class Data Demos on Google Sheets page
Lecture 0: Welcome (PPT)
Lecture 1: What is Probability? (PPT)
- Khan Academy Practice: Simple Probabilities
- Khan Academy Practice: Comparing Probabilities
- Khan Academy Practice: Subsets
- Khan Academy Practice: Basic Set Notations
- Khan Academy Practice: Conditional Probability
- A short animation about conditional probability, also known as Bayes' Rule, by Harvard's Stat110x course.
- Khan Academy Practice: Addition Rule
- Khan Academy Practice: Adding Probabilities
- Khan Academy Quiz 1
- Khan Academy Practice: Independent Probabilities
- Khan Academy Practice: Dependent Probabilities
- Khan Academy Quiz 2
Case Study: Using Probability in Search-and-Rescue Operations | Prediction by the Numbers (PBS LearningMedia for Teachers)
Self-Assessments
- Khan Academy Final Test
- Exercise Problems from Instructor (Download PPT to see solution in the notes section)
Chapter 3, Introductory Statistics by the openStax at Rice University
Probability course on Khan Academy
Comprehensive cheat sheet on all things probability
Besides probability, you are also expected to be comfortable with these two additional topics:
- Algebra: If your mathematics is a little rusty, I encourage you to brush up on your algebra skills before you arrive. There are on-line resources available to you at Khan Academy and WooTube. The summer MBA bootcamp will also cover important math skills, including Greek letters for mathematics, and logarithm, which we will use extensively in the course.
- Excel: The summer MBA bootcamp covers essential Excel skills you will need for this course. You should also use Lynda.com tutorials as needed.
Most importantly, you should begin to pay attention to data analysis in business news and literature. Listen to the Freakconomics and Stats + Stories podcasts regularly, check out the Harvard Data Science Review, and read a couple of relevant books, such as The Signal and the Noise, Moneyball, Freakonomics, Superfreakonomics, Superforecasting, Thinking Fast and Slow, Noise, and Naked Statistics.