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所在平台: Udemy |
课程主页: https://www.udemy.com/course/beginning-probability/
课程评论：没有评论
课程名称：初级概率论 课程概述：通过概率科学，将模糊的术语如“可能性”转化为可以用于评估风险和选择的精确值。本初级课程将为您提供将概率应用于现实世界问题所需的所有知识。您将学习如何使用贝叶斯定理结合外部世界的信息，结合简单概率以找出复杂事件的可能性。使用条件概率集中于特定群体或情境。通过条件概率得出正确的结论，包括假阳性和假阴性，避免常见的概率误区，防止错误决策。课程中包括知识练习和一些具有挑战性的练习（提供解决方案），以及公式“备忘单”和可选电子表格。 您将学习到：概率既是一门科学，也是一个可能性度量。课程将超越传统的扑克牌和骰子示例，讨论概率在天气预测或医学测试中的意义。概率有助于提供预期值，即您所期望的平均结果。然而，在随机事件模拟中，我们会意识到也需要预见意外情况。 概率看似简单明了，这使得人们容易被各种常见概率误区所误导。一种关键的误区是看到并不存在的模式。您将看到在普通随机情况下得出的荒谬结论的示例。另一种误区是混淆条件概率的逆。这会导致在评估医学测试结果时的混淆以及错误的因果关系。 讲师介绍：Carol Jacoby博士在过去的30多年里使用各种分析方法来回答复杂问题。在Hughes Electronics和其他公司担任任务分析师期间，她预测结果并进行替代方案比较，涉及的应用广泛且定义模糊。她拥有数学博士学位，并在20年来通过主要大学教授技术课程。学员们称赞她的热情和使复杂主题变得清晰的能力。 如果您准备好深入数据并学习概率，请立即报名。若想先了解课程，可以查看简短的宣传视频或一些免费课程。期待在课堂上见到您！
Use 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.
