Want to solve a murder mystery? What caused your computer to fail? Who can you trust in your everyday life? In this course, you will learn how to analyze and assess five common forms of inductive arguments: generalizations from samples, applications of generalizations, inference to the best explanation, arguments from analogy, and causal reasoning. The course closes by showing how you can use probability to help make decisions of all sorts.
Think Again III: How to Reason Inductively
This course is part of Introduction to Logic and Critical Thinking Specialization
Taught in English
Some content may not be translated
Instructors: Dr. Walter Sinnott-Armstrong
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There are 5 modules in this course
Welcome to Think Again: How to Reason Inductively! This course is the third in the specialization Introduction to Logic and Critical Thinking, based on our original Coursera course titled Think Again: How to Reason and Argue. We are excited that you are taking this course, and we hope that you will take all four courses in the series, because there is a great deal of important material to learn. In the series as a whole, you learn how to analyze and evaluate arguments and how to avoid common mistakes in reasoning. These important skills will be useful to you in deciding what to believe and what to do in all areas of your life. The first part of this course introduces the series and the course. It also clarifies some peculiarities you may find with this course. We encourage you to watch the "Introduction to the Specialization" video first as it will help you learn more from the materials that come later.
What's included
1 video1 reading
<p><b>CONTENT</b>: This week begins by distinguishing inductive arguments from deductive arguments. Then we discuss four common forms of inductive argument: generalizations from samples (such as in political polls), applications of generalizations to particular cases (such as in predicting weather on a certain day), inferences to the best explanation (such as in using evidence to determine who committed a crime), and arguments from analogy (such as in identifying the use of one archaeological artifact by comparing it to other artifacts). We will expose the most common mistakes in these kinds of reasoning. Some of the "lectures" this week are a bit experimental (and perhaps weird!), as you will see. We hope that you enjoy them.<p><b>LEARNING OUTCOMES</b>: By the end of this week's material you will be able to do:<ul> <li>distinguish inductive from deductive arguments</li> <li>classify inductive arguments into five kinds</li> <li>identify and evaluate arguments that generalize from samples</li><li>identify and evaluate arguments that apply generalizations to cases</li><li>identify and evaluate inferences to the best explanation by applying standards that good explanations must meet</li><li>identify and evaluate arguments from analogy</li></ul></p><p><b>OPTIONAL READING</b>: If you want more examples or more detailed discussions of these kinds of inductive arguments, we recommend <em>Understanding Arguments, Ninth Edition</em>, Chapters 8 and 9.</p>
What's included
9 videos8 quizzes13 discussion prompts
<p><b>CONTENT</b>: This module will focus on how to decide what causes what. Students will learn how to distinguish necessary conditions from sufficient conditions and how to use data to test hypotheses about what is and what is not a necessary condition or a sufficient condition. Then we will distinguish causation from correlation (or concomitant variation) and explain the fallacy of post hoc ergo propter hoc. It is sad that some diners had to die to make this lesson possible, as you will see.</p> <p><b>LEARNING OUTCOMES</b>: By the end of this week’s material you will be able to do: <ul> <li> analyze causal reasoning</li> <li>distinguish necessary from sufficient conditions</li> <li>determine what is necessary or sufficient for what</li> <li>separate causation from correlation</li> </ul> </p> <p><b>OPTIONAL READING</b>: If you want more examples or more detailed discussions of these topics, we recommend <em>Understanding Arguments, Ninth Edition</em>, Chapter 10.</p>
What's included
9 videos8 quizzes7 discussion prompts
<p><b>CONTENT</b>: This week will cover chance and choice—in other words, probability and decision making. Probability is useful for measuring the strength of inductive arguments and also for deciding what to believe and what to do. You will learn about the nature and kinds of probability along with four simple rules for calculating probabilities. An optional honors lecture will then explain Bayes’ theorem and the common mistake of overlooking the base rate. Next we will use probabilities to evaluate decisions by figuring their expected financial value and contrasting financial value with overall value. </p><p><b>LEARNING OUTCOMES</b>: By the end of this week’s material, you will be able to do: <ul><li> solve some classic paradoxes of probability</li><li>apply simple rules of probability</li><li>use Bayes’ theorem to calculate conditional probabilities</li><li>avoid fallacies of probability</li><li>apply probabilities to calculate expected financial values</li><li>distinguish financial value from overall value</li><li>use simple rules to aid decisions under uncertainty</li></ul></p><p><b>OPTIONAL READING</b>: If you want more examples or more detailed discussions of these topics, we recommend<em> Understanding Arguments, Ninth Edition</em>, Chapters 11 and 12
What's included
10 videos9 quizzes10 discussion prompts
<p>This week gives you time to catch up and review, because we realize that the previous weeks include a great deal of challenging material. It will also be provide enough time to take the final quiz as often as you want, with different questions each time. </p><p>We explain the answers in each exam so that you can learn more and do better when you try the exam again. You may take the quiz as many times as you want in order to learn more and do better, with different questions each time. You will be able to retake the quiz three times every eight hours. You might not need to take more than one version of the exam if you do well enough on your first try. That is up to you. However many versions you take, we hope that all of the exams will provide additional learning experiences. </p>
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Frequently asked questions
How to solve a murder mystery.
“I'd like to thank both professors for the course. It was fun, instructive, and I loved the input from people from all over the world, with their different views and backgrounds.”
“Somewhere in the first couple weeks of the course, I was ruminating over some concept or perhaps over one of the homework exercises and suddenly it occurred to me, "'Is this what thinking is?" Just to clarify, I come from a thinking family and have thought a lot about various concepts and issues throughout my life and career...but somehow I realized that, even though I seemed to be thinking all the time, I hadn't been doing this type of thinking for quite some time...so, thanks!”
“The rapport between Dr. Sinott-Armstrong and Dr. Neta and their senses of humor made the lectures engaging and enjoyable. Their passion for the subject was apparent and they were patient and thorough in their explanations.”
No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.