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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/mindware
课程评论：没有评论
课程名称：思维工具：信息时代的批判性思维 课程概述： 在当今社会，大多数职业不仅需要一般智力，还需要具备收集、分析和思考数据的能力。个人生活中，当这些技能应用于日常涉及判断和选择的问题时，生活也会更加丰富。本课程介绍了统计学、概率论、科学方法论、认知心理学和成本效益理论的基本概念，并展示这些概念如何应用于选择产品、批判媒体对科学研究的报道等方方面面。概念简要明了，并通过商业、媒体和日常生活中的多个例子进行应用。 学习内容： - 了解为什么对求职者面试通常是个错误。 - 探讨在新餐厅首次就餐若非常美味，接下来的餐食不太可能同样出色的原因。 - 了解经济学家为何会在观看电影时走开或不吃餐厅食物。 - 探索为何登上《体育画报》封面的运动员往往在随后的赛季表现失望。 - 认识到虽然检测结果呈阳性，您可能并没有某种疾病的可能性。 - 了解到，若要知道咖啡对您的影响，需要通过抛硬币来决定是否在某天喝咖啡来实验。 - 分析为何拥有自己办公楼的办公室可能是个错误。 - 讨论为何不应该持有下跌的股票以期望其反弹，从而避免损失。 - 揭示媒体中大量健康信息为何是误导性的。 课程大纲： 1. 引言：探讨个人和文化如何通过提高智力应对信息时代的挑战，并介绍所需的新技能。 2. 第一课：统计学基础概念，包括变量、正态分布、标准差等，并通过实际例子展示其应用。 3. 第二课：大数法则，教授如何判断数据的充足性及处理误差的方法。 4. 第三课：相关性，学习如何准确评估变量之间的关系，避免虚假相关。 5. 第四课：实验，理解为何实验提供因果关系更有力的证据，并了解如何设计实验。 6. 第五课：预测，认识预测未来时的系统性错误及如何考虑基率。 7. 第六课：认知偏差，探讨我们的决策如何受到心智模型的影响，以及常见的判断错误。 8. 第七课：选择与决策，学习如何进行成本效益分析以及避免不良决策。 9. 第八课：逻辑与辩证推理，介绍归纳逻辑与演绎逻辑的区别以及常见逻辑错误。 10. 结论：总结所学内容及其在实际生活中的应用。 该课程旨在帮助学员提升批判性思维能力，以便更有效地面对信息时代的复杂性。
Name:Introduction
Description:Individuals and cultures can make themselves smarter. Since the beginning of the Industrial Revolution, people have become enormously smarter. The Information Age requires a brand-new set of skills involving statistics, probability, cost-benefit analysis, principles of cognitive psychology, logic and dialectical reasoning.
Name:Lesson 1: Statistics
Description:Basic concepts of statistics and probability including the concepts of variable, normal distribution, standard deviation, correlation, reliability, validity, and effect size. Concrete examples are drawn from everyday life and show how the concepts can be used to solve ordinary problems.
Name:Lesson 2: The Law of Large Numbers
Description:How to think about events in such a way that they can be counted and a decision can be made about how much data is enough. You will learn about the concept of error variance and how it can be combatted by obtaining multiple observations. Your will learn that your judgments about people’s personalities are prone to serious errors that are largely avoided for judgments about abilities. And you will discover why it’s usually a mistake to interview job applicants.
Name:Lesson 3: Correlation
Description:It can be extremely difficult to make an accurate assessment of how two variables are related to one another; prior beliefs can be more important than data in estimating the strength of a given relationship. You will learn simple tools to estimate degree of association. You will learn about the nature of illusory correlations and how to avoid them. You will learn about the concepts of confounded variable and self-selection error.
Name:Lesson 4: Experiments
Description:You will learn that correlations can only rarely provide conclusive evidence about whether one variable exerts a causal influence on another and why experiments provide far better evidence about causality than correlations. You will be shown how to conduct experiments in business settings and experiments on yourself. You will learn the distinction between within subject designs and between subject designs. You will learn about the concept of artifacts and some tricks for avoiding them. You will learn how to discover natural experiments.
Name:Lesson 5: Prediction
Description:You will learn about the kinds of systematic errors we make when trying to predict the future. You will learn about regression to the mean and why you should assume that extreme values on a variable will be less extreme when next observed. You will learn how to think about observations in terms of true score plus error. You will learn about the concept of base rate and why it must be taken into account when estimating probabilities of specific events.
Name:Lesson 6: Cognitive Biases
Description:We understand the world not through direct perception but through inferential procedures that we are unaware of. Our understanding of the world is heavily influenced by schemas or abstract representations of events. We are prone to serious judgment errors that can be avoided to a degree when we understand their basis. We make guesses about probability and causality by applying the representativeness heuristic based on similarity assessments which can be very misleading. We make judgments about frequency and probability by relying in part on the availability heuristic, judging things as frequent or probable to the degree that instances come readily to mind.
Name:Lesson 7: Choosing and Deciding
Description:How to conduct a cost-benefit analysis. Why you should throw the analysis away after doing it if the decision is personal and very important. How to avoid throwing good money after bad. How to avoid doing something that will prevent you from doing something more valuable. Why it can be expensive to try to avoid the possibility of loss. Why incentives can backfire.
Name:Lesson 8: Logic and Dialectical Reasoning
Description:The distinction between inductive logic and deductive logic. Syllogisms. Conditional reasoning. The distinction between truth of an argument and validity of an argument. The concepts of necessity and sufficiency. Venn diagrams. Common logical errors. When to avoid contradiction and when to embrace it, how to avoid undue certainty about judgments and decisions, and why attention to context rather than form is crucial for analysis of most real-world problems.
Name:Conclusion
Description:
Most professions these days require more than general intelligence. They require in addition the ability to collect, analyze and think about data. Personal life is enriched when these same skills are applied to problems in everyday life involving judgment and choice. This course presents basic concepts from statistics, probability, scientific methodology, cognitive psychology and cost-benefit theory and shows how they can be applied to everything from picking one product over another to critiquing media accounts of scientific research. Concepts are defined briefly and breezily and then applied to many examples drawn from business, the media and everyday life. What kinds of things will you learn? Why it’s usually a mistake to interview people for a job. Why it’s highly unlikely that, if your first meal in a new restaurant is excellent, you will find the next meal to be as good. Why economists regularly walk out of movies and leave restaurant food uneaten. Why getting your picture on the cover of Sports Illustrated usually means your next season is going to be a disappointment. Why you might not have a disease even though you’ve tested positive for it. Why you’re never going to know how coffee affects you unless you conduct an experiment in which you flip a coin to determine whether you will have coffee on a given day. Why it might be a mistake to use an office in a building you own as opposed to having your office in someone else’s building. Why you should never keep a stock that’s going down in hopes that it will go back up and prevent you from losing any of your initial investment. Why it is that a great deal of health information presented in the media is misinformation.
