©2007 by the mcgraw-hill companies, inc. all rights reserved. analyzing and evaluating inductive...

©2007 by The McGraw-Hill Companies, Inc. All rights reserved.

Analyzing and Evaluating Inductive Arguments

The aim of this tutorial is to help you learn to analyze and

evaluate causal arguments.

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Like all other arguments, inductive arguments try to prove a conclusion by offering premises which, if true, support the truth of the conclusion.

The key difference between inductive and deductive arguments is that true premises in a strong inductive argument offer a high probability that the conclusion is true, while true premises in a valid deductive argument guarantee the truth of the conclusion.

Thus, evaluating inductive arguments depends on assessing this probability.

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Before we can evaluate an argument, we need to analyze it. We need to be clear what the argument is trying to prove, what evidence it uses, and how it relates this evidence to its conclusion.

Causal arguments deal with causal claims. They argue that one thing caused another thing to happen. Just as with analogies, the key to analyzing causal arguments is to clearly define the two things and their relationship.

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There are two basic kinds of causal arguments; that is, two standard forms into which causal arguments can be translated.

Only Relevant Difference: This form argues that “X” caused “Y” because “X” is the only difference between this case where “Y” occurred and other cases where “Y” did not occur.

The key issue in evaluating this form is knowing whether or not, in fact, “X” was the only relevant difference between the cases.

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Only Relevant Common Thread: This form argues that “X” caused “Y” because “X” is the only common factor in multiple cases where “Y” occurred.

The key issues in evaluating this form are

(1) knowing whether or not, in fact, “X” was the only common factor and

(2) determining how likely that the two or more cases of “Y” were caused by independent causes.

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As with analogies and other types of inductive arguments, causal arguments are not often easy to evaluate objectively.

Most often, the best you can do is assess the relative strength of a causal argument by considering how well it fares when potential short-falls are considered.

There are several typical problems that befall causal arguments. After analyzing your causal argument, think carefully about whether or not it exhibits any of these problems.

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1. Post Hoc, Ergo Propter Hoc

This is Latin for “after this, therefore because of this.” This mistake assumes that proximity in time between two events is evidence for a causal connection.

2. Ignoring a Possible Common Cause

This mistake happens when we think “X” caused “Y” when, in fact, both “X” and “Y” were caused by “Z.”

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3. Assuming a Common Cause

Most basically this mistake discounts the possibility of coincidence. In this way it is similar to the Post Hoc fallacy. Additionally, when two events happen we should not assume that they have the same cause.

4. Reverse Causation

This mistake happens when terms in a causal argument are reversed. Thus, someone argues that “X” caused “Y” when, in fact, “Y” caused “X.”

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Unlike determining the validity or invalidity of a deductive argument, evaluating an inductive argument like a causal argument can be somewhat subjective.

Instead of immediately trying to determine in some objective way a causal argument’s absolute strength, it is prudent to evaluate it by determining whether or not it exhibits one or more of the common causal fallacies.

Some causal arguments permit a more objective measurement of strength. For these look at the Causation in Population section of the text.

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Look at the people who ride the early morning bus: tired, depressed. Riding the bus must be bad for you.

This is an example of the “X is the common thread” form of causal argument. Lots of people looking depressed and tired, the common thread being that they are all on the bus.

Is this a post hoc fallacy? Is it assuming a common cause?

Is it ignoring a common cause?

Could it be an example of reverse causation?

Is the bus the only common thread at work here?

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Is it a post hoc argument? Well, we want to be sure that the the relationship in time between people riding the bus and their being tired and depressed wasn’t the only proof.

Is there a common cause? Maybe they are riding the morning bus and tired and depressed because they had to get to work early.

Could they be riding the bus because they are too tired and depressed to walk? Hmmm.

Could it be a mere coincidence that they are on the bus and tired and depressed? Yes, it could.

This is a weak argument. There are many potential problems with it that would need to be investigated before giving much credence to it.

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Most cocaine users have, at some point, smoked marijuana regularly. Therefore, smoking marijuana causes cocaine use.

This is another example of the “X is the common thread” form of causal argument. Lots of people using cocaine and most have a common past habit of smoking marijuana.

Is this a post hoc fallacy? Is it assuming a common cause?

Is it ignoring a common cause?

Could it be an example of reverse causation?

Is marijuana use the only common thread at work here?

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Is there a common cause? Maybe the people use cocaine and marijuana to escape from their problems. Maybe some underlying medical condition causes both cravings. Maybe these people have risk-taking tendencies that cause both.

A backwards fallacy? If all we know is that they use both cocaine and marijuana we’d have to be very careful about the possibility.

Could it be a mere coincidence that they used marijuana and cocaine? Well, it could be but it seems unlikely, especially if there are lots of people being considered.

This is a weak argument. There are many potential problems with it that would need to be investigated before giving much credence to it.

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From these simple examples you can see the process of analyzing and evaluating causal arguments. If you are diligent about applying the evaluation guidelines you’ll find success with analogies.

Remember, no inductive argument is perfect. If you demand perfection or near perfection in them, you’ll never find a strong one. You should be critical but realistic when evaluating inductive arguments.

This is the end of the tutorial.

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©2007 by the mcgraw-hill companies, inc. all rights reserved. analyzing and evaluating inductive...

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