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所在平台: Udemy |
课程主页: https://www.udemy.com/course/statistical-thinking/
课程评论：没有评论
课程名称：统计思维与认知偏见基础 概述：您想更清晰地看待世界吗？想学会像统计学家一样思考，对周围的数字提出质疑吗？通过这门课程，您将学会在工作、投资和生活中做出更好的决策。本课程并不是传统统计学的入门课，数学内容非常少，您不需要完成大量的数学题。课程的重点将放在统计学的直觉和实际应用上，以帮助您做出更好的判断。 我们将探讨统计学的基本理念和概念，结合日常例子，例如：如果相关性并不等于因果关系，那到底是什么？人类是否真的消灭了60%的动物？90%的牙医真的推荐这款牙膏吗？您将学习如何不被数据可视化所迷惑，理解概率如何改变您对刑事起诉和金融危机等问题的看法。 课程分为两大部分，深入探讨认知偏见和汉斯·罗斯林的事实思维。我们固有的心理偏见会影响我们解读每天遇到的统计数据的方式，无论是新闻、社交媒体还是广告。本部分的目标是学习如何识别这些逻辑谬误，从而以更客观的方式解读周围的世界。 在倒数第二部分，我们将遇到推断与因果关系的复杂世界，以及统计学的工作马——回归分析。这一部分将探讨从购买苹果到P值操纵，再到医生约翰·伊奥尼斯所言“发表的研究结果大多数是错误的”的原因。 最后一部分将关注预测与预测，探讨为何预测会失败、如何才能成功，以及完美预测是否可能（或者确实是可取的）。在信息唾手可得的时代，具备统计思维的能力是21世纪每个人必备的技能。正如赫伯特·乔治·威尔士所说：“统计思维有朝一日将和阅读与写作一样成为有效公民所必需的技能”——这一时刻已然到来。
Do you want to see the world more clearly? Learn to think like a statistician and question the numbers all around you? Make better decisions at work, when investing, and in life? Then you are in the right place.This course is not a regular introduction to statistics. There will be very little math so you won't be asked to complete lots of mathematical problem sets. The focus of the course will be on the intuition and practical application of statistics in making better decisions and judgments. We will explore the fundamental ideas and concepts of statistics but with with everyday examples, answering questions such as: if correlation does not equal causation, then what does? have humans really wiped out 60 percent of animals? and do 9 out of 10 dentists actually recommend this toothpaste?You will learn how not to be fooled by data visualizations, and how an understanding of probability can change the way you view everything from prosecuting criminals to financial crises.The course has two sections diving into the world of cognitive bias and the work of Hans Rosling on Factfulness thinking. Our inherent mental biases can affect the way we perceive and interact with the statistics we encounter every day; whether in the news, on social media, or in advertisements. The goal of this section is to learn how to spot these logical fallacies so we can keep them at bay and interpret the world around us more objectively.In the penultimate section, we shall encounter the tricky world of inference, causation, and the trusty work-horse of statistics; regression analysis. This section will explore everything from buying apples, to p-hacking, and to what caused physician John Ioannidis to proclaim that "most published research findings are false".The final section will look at prediction and forecasting; exploring why predictions fail, how they can succeed, and if perfect prediction will ever be possible (or indeed desirable).With a world of information now at our fingertips, being able to think statistically is an essential skill for all those living in the 21st century. Indeed as Herbert George Wells said, "statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write" - and that day has come.
