Reasoning Skills and Jumping to Conclusions Help (page 2)
Introduction to Reasoning Skills and Jumping to Conclusions
"'To be sure,' said Canby; 'you're on the Island of Conclusions. Make yourself at home. You're apt to be here for some time.'
'But how did we get here?' asked Milo, who was still a bit puzzled by being there at all.
'You jumped, of course,' explained Canby. 'That's the way most everyone gets here. It's really quite simple; every time you decide something without having a good reason, you jump to Conclusions whether you like it or not. It's such an easy trip to make that I've been here hundreds of times.'"
—The Phantom Tollbooth by Norton Juster (1961, Random House)
Just as there are logical fallacies to beware of in deductive reasoning, there are several logical fallacies to look out for in inductive reasoning. This lesson will show you how to recognize and avoid those fallacies.
Imagine a coworker of yours, Dennis, bumps into you during a coffee break. "You know, I tried the coffee at the new deli this morning," he says, "and it was lousy. What a shame, the new deli stinks."
Oops. Dennis has just been caught jumping to conclusions.
Inductive reasoning, as you know, is all about drawing conclusions from evidence. But sometimes, people draw conclusions that aren't quite logical. That is, conclusions are drawn too quickly or are based on the wrong kind of evidence. This lesson will introduce you to the three logical fallacies that lead to illogical conclusions in inductive reasoning: hasty generalizations, biased generalizations, and non sequiturs.
A hasty generalization is a conclusion that is based on too little evidence. Dennis's conclusion about the new deli is a perfect example. He'd only been to the new deli once, and he'd only tried one item. Has he given the deli a fair chance? No. First of all, he's only tried the coffee, and he's only tried it one time. He needs to have the coffee a few more times before he can fairly determine whether or not their coffee is any good. Second, he needs to try their other foods as well before he can pass judgment on the whole establishment. Only after he has collected this "evidence" will he have enough premises to lead to a logical conclusion.
Here's another example of a hasty generalization. Let's say you're introduced to a woman named Ellen at work, and she barely acknowledges you. You decide she's cold and arrogant. Is your conclusion fair? Maybe Ellen was preoccupied. Maybe she was sick. Maybe she had a big meeting she was heading to. Who knows? The point is, you only met her once, and you drew a conclusion about her based on too little evidence.
A few weeks later, you meet Ellen again. This time, she's friendly. She remembers meeting you, and you have a pleasant conversation. Suddenly you have to revise your conclusion about her, don't you? Now you think she's nice. But the next time you see her, she doesn't even say hello. What's happening here? You keep jumping to conclusions about Ellen. But you really need to have a sufficient number of encounters with her before you can come to any conclusions.
Hasty generalizations have a lot in common with stereotypes. In the case of stereotypes, conclusions about an entire group are drawn based upon a small segment of that group. Likewise, hasty generalizations draw conclusions about something based on too small a sample, such as one cup of coffee, or two or three encounters with Ellen.
Here are a few more hasty generalizations:
Brandon is a jock, and he's a lousy student. All jocks are lousy students.
Suzie is blonde, and she has a lot of fun. So I guess it's true that blondes have more fun.
You'd need to see a lot more examples of jocks and blondes before either of these conclusions could be justified.
We make hasty generalizations all the time. The man on the bus did a double take when you climbed on so your outfit must look weird. Your boss didn't respond to you when you said "Good morning" so you must be next to get fired. The book your teacher asked you to read looks boring so you will hate it. The cloud just went under the sun so it's going to pour any minute. Making decisions without enough evidence usually leads to mistakes, both big and small.
On a local TV program, you hear that a recent poll shows that 85 percent of people surveyed support drilling for oil in Alaska's Arctic National Wildlife Refuge. If most Americans feel this way, you think that maybe you should rethink your position on the issue. Unfortunately, what you haven't been told is that the only people who were surveyed for this poll were employees of major oil companies.
The problem with a survey like this is that the pool of people it surveyed was biased. Think about it for a moment. Employees of oil companies are going to favor drilling for oil because it will generate revenue for the oil companies, which in turn means job security for the employees. Therefore, the conclusion that the majority of Americans favor drilling for oil in Alaska's Arctic National Wildlife Refuge is biased as well. It's based on a survey of biased respondents and, as a result, cannot be considered representative of Americans as a whole.
Biased generalizations can be made without using surveys as well. Any conclusion based on the testimony of someone who is biased is a biased generalization. For example, imagine you tell a friend that you're taking a class next fall with Professor Jenkins.
"Professor Jenkins?!" your friend replies. "She's terrible. I got an F in her class."
Should your friend's reaction change your mind about taking the class? Probably not. Your reasoning skills should tell you that your friend's conclusion about Professor Jenkins might be biased. If he got an F in her class, he isn't likely to have a very good opinion of her.
Let's look at another example. Read the following inductive argument carefully:
All of my friends say fraternities are a waste of time. So I guess you shouldn't bother trying to join one if you don't want to waste your time.
How could this be a biased generalization? Write your answer below.
If this conclusion is based on evidence from biased sources, then the generalization (the conclusion) is biased. For example, if those friends who say that fraternities are a waste of time are also friends who had wanted to be in a fraternity but had not been invited to join, then they're likely to have a negative (biased) opinion of fraternities. Hence, their conclusion would be biased.
On the other hand, how could this be a reliable inductive argument? Write your answer below.
If all the friends were members of a fraternity, then this would be a much more reliable conclusion. If all the friends were members of different fraternities rather than the same one, it'd be even more reliable; their conclusion would represent a broader range of experience.
To avoid being biased, then, conclusions should be drawn only from a sample that's truly representative of the subject at hand. An inductive argument about student involvement on campus, for example, should be based on evidence from all types of students, not just those on the Student Affairs Committee.
A non sequitur is a conclusion that does not follow logically from its premises. The problem with this fallacy is that too much of a jump is made between the premises and the conclusion. Here's an example:
Johnson is a good family man. Therefore, he will be a good politician.
It's great that Johnson is a good family man, but his devotion to his family does not necessarily mean that he'll be a good politician. Notice that this argument assumes that the qualities that make "a good family man" also make a good politician—and that's not necessarily, or even probably, the case. Many good family men are lousy politicians, and many good politicians are not particularly devoted to their families. The argument makes a leap—a big one—that defies logic. It's certainly possible that Johnson will be a good politician, but solely judging from the premises, it's not likely.
Here's another example of a non sequitur:
Josie is left-handed, so she'd be a good artist.
This non sequitur assumes that left-handed people are more artistic than right-handed people. This may sometimes be true, but it is not always the case. Furthermore, even if she is artistic, being a good artist requires inspiration and dedication, and we have no evidence that Josie has those qualities. Therefore, we can't logically conclude that Josie will be a good artist.
Here's one more:
You like cats. Cathy is a cat person, too, so you'll get along well.
What's wrong with this argument? Here, the arguer assumes that because you and Cathy are both "cat people," you will get along. But just because you both like cats doesn't mean you'll like each other. It's another non sequitur.
Some non sequiturs follow the pattern of reversing the premise and conclusion. Read the following argument, for example:
People who succeed always have clear goals. Sandra has clear goals, so she'll succeed.
Here's the argument broken down:
- Premise 1: People who succeed always have clear goals.
- Premise 2: Sandra has clear goals.
- Conclusion: Sandra will succeed.
Though at first glance, the example may seem reasonable, in actuality, it doesn't make logical sense. That's because premise 2 and the conclusion reverse the claim set forth in premise 1. When parts of a claim are reversed, the argument does not stay the same. It's like saying that geniuses often have trouble in school, so someone who is having trouble in school is going to be a genius, and that's just not logical.
In Sandra's case, your critical thinking and reasoning skills should also tell you that simply because she set clear goals for herself doesn't mean they'll be achieved; hard work and dedication are also factors in the formula for success. Furthermore, the definition of success is something everyone determines for him or herself.
Assuming almost always gets a person in trouble. Think twice—or even three times—before you jump to conclusions. You may regret the trip.
Reasoning Skills and Jumping to Conclusions In Short
When it comes to inductive arguments, you need to be on the lookout for three kinds of logical fallacies. Hasty generalizations draw conclusions from too little evidence. Biased generalizations, on the other hand, draw conclusions from biased evidence. Finally, non sequiturs jump to conclusions that defy logic; they make assumptions that don't hold water.
Skill Building until Next Time
- The next time you meet someone for the first time, be aware of how you form an opinion of him or her. Do you jump to conclusions, or do you wait until you've gathered more evidence to decide whether or not he or she would make a good friend or colleague?
- Teach a friend what you learned in this lesson. Give your friend a few of your own examples of the three fallacies.
Exercises for this concept can be found at Jumping to Conclusion Help.
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