Beginning Probability

Avoid the probability fallacies that often mislead peopleCalculate probabilities using cases and historical dataCalculate the probabilities of complex events based on simpler onesApply Bayes’ Rule to bring outside knowledge into your probability estimatesUse expected value to assess and compare alternativesFocus your analysis on segments or situations using conditional probabilityReason correctly using false positives and false negativesDevelop intuition about randomnessUse the science of probability to turn vague terms such as likely into precise values you can use to assess risks and alternatives. This beginning course gives you all you need to apply probability to real-world questions. Use Bayes’ Rule to incorporate what you know about the outside world. Combine simple probabilities to find the likelihood of complex events. Use conditional probability to focus on groups or situations. Draw correct conclusions from conditional probabilities, including false positives and false negatives. Avoid the many probability fallacies that often lead to bad decisions. Try out your knowledge in exercises, then take on some tricky challenges (you’ll get the solutions). A formula “cheat sheet” and optional spreadsheets are included.What You’ll LearnProbability is both a science and a measure of likelihood. We go beyond the standard examples of cards and dice and discuss what it means for weather prediction or medical tests. Probability is useful for giving you an expected value, what you would expect the outcome to be on average. Yet, as we watch random events play out in a simulation, we see that we need to also expect the unexpected.Probability appears simple and straightforward, which leads people to get misled by various common probability fallacies. One key fallacy is seeing patterns that aren’t there. You will see examples in which ordinary randomness leads to silly conclusions. Another is the confusion of the inverse of conditional probabilities. This causes confusion in assessing the results of medical tests and making faulty causal connections.From Your Instructor, Carol JacobyI’ve been using various types of analysis to answer tricky questions for over 30 years. I did this as a mission analyst at Hughes Electronics and other companies to predict outcomes and compare alternatives. The applications were broad and ill-defined: protect Europe from missile attack, limit drug smuggling, design a highway system for self-driving cars and more. I have a PhD in mathematics, and I’ve been teaching technical classes to managers through major universities for 20 years. The students praise my enthusiasm and ability to make complex subjects clear. A common comment is, I wish you had been my math teacher in high school. Here are samples of classes that were heavy in analysis.· Predictive Analytics: Caltech Center for Technology and Management Education· Lean Six Sigma: Caltech Center for Technology and Management Education· Systems Engineering: UCLA Extension for Raytheon· The Decisive Manager: UCLA Technical Management ProgramOne thing I like about teaching is interacting with the students. I look forward to comments and direct messages and respond promptly. Any feedback is encouraged. If something is confusing or doesn’t work as expected, I want to hear about it right away so I can fix it. I especially want to hear about your own data explorations and other topics you’d like to learn about or problems you’d like to solve.So, are you ready to dig into that data and see what you can learn? Learn probability in just a couple hours. Sign up now. If you want more of a taste first, check out the quick promo video or some of the free lessons. I hope to see you in class.Who this course is for:Beginner interested in more precise likelihood predictionBeginner who needs a probability foundation for statistics, risk analysis, data science or other more advanced analysis.