What are Logical Fallacies That Incorporate Cause-And-Effect Mistakes?

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Logical fallacies are errors of reason that can occur in inductive reasoning. Since inductive reasoning moves from the particular to the general, it is important to determine how much and what kind of evidence you need to make a valid argument. Failure to have proper evidence is linked to several kinds of logical fallacies.

Since logic is one of the main techniques used in persuasion, being able to identify and discount logical fallacies in others' arguments and avoid making them in one's own arguments are both important. One of the things that can undermine logic is making mistakes in relating cause and effect. There are several errors that one can make in arguing cause and effect, and the following fallacies of cause and effect occur so frequently that they are named.

Gambler's Due: The gambler's due fallacy assumes that the expectation of an event is increased after a number of times that it fails to occur, whereas the probability is, in fact, the same for each separate occurrence. An example is: Of course I'm going to buy another lottery ticket -- I haven't won anything all year, and I'm due. This is a logical fallacy of cause and effect because the probability of winning today is not causally related to not having won on prior days, even many prior days. Losing does not subsequently cause winning.

Post hoc ergo propter hoc: Assuming that sequence indicates causality is the mistake made by this Latin-named fallacy. Translated, the name means "after, therefore caused by." An example is: My cousin drank the town water and got leukemia. It must be the town water that caused her illness. The sequence of drinking town water and subsequently falling ill from leukemia does not in and of itself lead to a valid conclusion that the water was the causal agent in the illness. Thus, this is a cause and effect fallacy.

Slippery slope. In this fallacy, there is an assumption that one event inevitably leads to specific results, when the causal chain is by no means clear. An example is: Borrow the car? Next thing, you'll be wanting your own car, and your own apartment! This argument fails to treat an individual case as an individual case, and assumes that the case in question will unquestionably follow a pattern that is claimed to exist. A request to borrow a car may, in fact, go no further than the objective explicitly stated. The claimed cause and effect relationship simply does not exist.


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Post 6

@stl156 - Interesting example. I was horrible at statistics, but I remember talking about correlation and causation. Since I had to stop and think about it myself, I think in your example, the correlation would be that good skis equal a winner, but the fact that the good skis won might have been caused by the better skier. What I did understand back in statistics and still know now is that to determine the difference, you would need to get a lot more people and preferably each have them use both types of skis. Then the statistics takes over and tells you whether one type of skis equals a faster time.

I think the thing about fallacies is that they

really, really annoy the people that understand them. This article is talking about cause and effect fallacies, but there are a whole slew of other ones. These here are more statistics and odds based, so maybe they are easier for people to grasp, but once you start getting into the other fallacies, most people fall into their traps all the time. I think politicians are the best at purposely using fallacies to mislead the people they are talking to or draw attention away from their own faults.
Post 5

When I was in college and grad school, I had to take a lot of statistics classes. There is a lot of time spent on the post hoc ergo propter hoc fallacy, even though I had never heard it referred to as that until I read this article. We always just referred to the difference between causation and correlation, which is basically what statistics are around to do. Scientists want to narrow in to find whether correlations actually are causations.

For example, you can take two skiers and give one top of the line skis and the other cheap, bargain skis. If the person with the expensive skis makes it to the bottom of the hill first, a lot

of people would just assume it's because the skis were better. It could be the case that the one with the better skis is also a professional skier, and the other is a beginner, so the professional might have won even with the bad skis. Because of things like that, a lot of statistics deals with parsing out those different things.
Post 4

@titans62 - By saying 4 girls isn't exactly the gambler's due kind of *is* saying it. Yes, there is a 1 in 16 chance of having 4 girls, but so is the chance of having a boy, girl, girl, boy. There are 16 possible combinations, so anyone who has 4 kids will have had a 1 in 16 chance of having those kids in that exact order.

The same thing can kind of work for the roulette board in the short run, but since casinos work in the long run it doesn't benefit them much. Yes, it might focus more people's money on a certain number once in a while, and then the chance of the ball landing somewhere without

money is greater, but eventually it will hit that number, and the casino will have to pay up. Really, the zeroes are what keeps roulette profitable for a casino.

The best one at a casino is the slot machines. They are programmed to pay out a certain amount, but I constantly hear people saying not to play a machine that just won big, because it won't hit again, which is completely wrong.

Post 3

@ElizaBennett - I agree. The gambler's due is pretty frustrating to see happen. At the same time, though, in the case of someone having a lot of the same sex of children, it is kind of longshot odds. Even though the probability of an individual birth being a female is 50%, the probability of a couple having 4 girls is 1 in 16, which is pretty rare.

The thing that really gets me, though, is how casinos have gone about putting up past numbers signs at almost every game that allows it. I think roulette is the big one, just because the game itself is pretty simple. I hear all the time people talking about a number that's going to

hit, because it hit 3 times already.

I reality, it's not really a trap, since the numbers have the same chance to hit every time, but I find myself basing my plays off of past numbers sometimes. It's just fun to do it and win, and claim you "had a feeling" about that number coming up for the 4th time.

Post 2

@MissDaphne - I agree with you that people don't use rigorous enough thinking. You see the Gambler's Due a lot in real life. If someone already has three little girls, for instance, people are more surprised to find out they're having a fourth girl than they would be to find out that someone is having their first girl.

But someone with no children - or with three boys - has exactly the same chance of having a girl as someone who already has *six* girls. Right about fifty percent! The odds "reset" every time. It's just that if you don't have any kids yet, your odds of having four girls in a row are quite low. With every girl you have, your odds of having four girls in a row go up.

Post 1

This article does a really nice job of defining these. I think that classes really need to spend more time teaching students to identify fuzzy thinking, because it certainly is all around.

For instance, you really see the Post Hoc fallacy in newspaper articles about studies. I saw one recently reporting a connection between teens using social media and teens drinking.

Now, that makes it sounds like social media *causes* kids to drink, but that evidence doesn't show that. Maybe both drinking and using social media are caused by the same factors - like kids having a lot of friends and being keen to impress them.

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