CRTS important notes!

I was found some notes from the internet, that is important for our CRTS in the final exam. Yes, Mr. Kantha was told us there have many questions about fallacies will coming out in exam. So I am now posting some important notes to here for make easier copy and paste.

Fallacies
In order to understand what a fallacy is, one must understand what an argument is. Very briefly, an argument consists of one or more premises and one conclusion. A premise is a statement (a sentence that is either true or false) that is offered in support of the claim being made, which is the conclusion (which is also a sentence that is either true or false).

There are two main types of arguments: deductive and inductive. A deductive argument is an argument such that the premises provide (or appear to provide) complete support for the conclusion. An inductive argument is an argument such that the premises provide (or appear to provide) some degree of support (but less than complete support) for the conclusion. If the premises actually provide the required degree of support for the conclusion, then the argument is a good one. A good deductive argument is known as a valid argument and is such that if all its premises are true, then its conclusion must be true. If all the argument is valid and actually has all true premises, then it is known as a sound argument. If it is invalid or has one or more false premises, it will be unsound. A good inductive argument is known as a strong (or "cogent") inductive argument. It is such that if the premises are true, the conclusion is likely to be true.

A fallacy is, very generally, an error in reasoning. This differs from a factual error, which is simply being wrong about the facts. To be more specific, a fallacy is an "argument" in which the premises given for the conclusion do not provide the needed degree of support. A deductive fallacy is a deductive argument that is invalid (it is such that it could have all true premises and still have a false conclusion). An inductive fallacy is less formal than a deductive fallacy. They are simply "arguments" which appear to be inductive arguments, but the premises do not provided enough support for the conclusion. In such cases, even if the premises were true, the conclusion would not be more likely to be true.

Four categories of fallacies:
a) Appeal to Emotion
b) The Impostors
c) Distracter & Disorders
d) Inductive Fallacies


Appeal to Emotion:
Scare tactics/ Appeal to fear
Appear to Flattery
Peer Pressure
Appeal to pity


Appeal to Fear
The Appeal to Fear is a fallacy with the following pattern:

Y is presented (a claim that is intended to produce fear).
Therefore claim X is true (a claim that is generally, but need not be, related to Y in some manner).
This line of "reasoning" is fallacious because creating fear in people does not constitute evidence for a claim.

It is important to distinguish between a rational reason to believe (RRB) (evidence) and a prudential reason to believe (PRB) (motivation). A RRB is evidence that objectively and logically supports the claim. A PRB is a reason to accept the belief because of some external factor (such as fear, a threat, or a benefit or harm that may stem from the belief) that is relevant to what a person values but is not relevant to the truth or falsity of the claim. For example, it might be prudent to not fail the son of your department chairperson because you fear he will make life tough for you. However, this does not provide evidence for the claim that the son deserves to pass the class.

Examples of Appeal to Fear
"You know, Professor Smith, I really need to get an A in this class. I'd like to stop by during your office hours later to discuss my grade. I'll be in your building anyways, visiting my father. He's your dean, by the way. I'll see you later."

"I don't think a Red Ryder BB rifle would make a good present for you. They are very dangerous and you'll put your eye out. Now, don't you agree that you should think of another gift idea?"

You must believe that God exists. After all, if you do not accept the existence of God, then you will face the horrors of hell."

"You shouldn't say such things against multiculturalism! If the chair heard what you were saying, you would never receive tenure. So, you had just better learn to accept that it is simply wrong to speak out against it."


Appeal to Flattery
An Appeal to Flattery is a fallacy of the following form:

Person A is flattered by person B.
Person B makes claim X.
Therefore X is true.
The basic idea behind this fallacy is that flattery is presented in the place of evidence for accepting a claim. this sort of "reasoning" is fallacious because flattery is not, in fact, evidence for a claim. This is especially clear in a case like this: "My Bill, that is a really nice tie. By the way, it is quite clear that one plus one is equal to forty three."

Examples of Appeal to Flattery
"Might I say that this is the best philosophy class I've ever taken. By the way, about those two points I need to get an A..."

"That was a wonderful joke about AIDS boss, and I agree with you that the damn liberals are wrecking the country. Now about my raise..."

"That was a singularly brilliant idea. I have never seen such a clear and eloquent defense of Plato's position. If you do not mind, I'll base my paper on it. Provided that you allow me a little extra time past the deadline to work on it."


Peer Pressure/ Bandwagon
The Bandwagon is a fallacy in which a threat of rejection by one's peers (or peer pressure) is substituted for evidence in an "argument." This line of "reasoning" has the following form:

Person P is pressured by his/her peers or threatened with rejection.
Therefore person P's claim X is false.
This line of "reasoning" is fallacious because peer pressure and threat of rejection do not constitute evidence for rejecting a claim. This is expecially clear in the following example:

Joe: "Bill, I know you think that 1+1=2. But we don't accept that sort of thing in our group. "
Bill: "I was just joking. Of course I don't believe that."

It is clear that the pressure from Bill's group has no bearing on the truth of the claim that 1+1=2.

It should be noted that loyalty to a group and the need to belong can give people very strong reasons to conform to the views and positions of those groups. Further, from a practical standpoint we must often compromise our beliefs in order to belong to groups. However, this feeling of loyalty or the need to belong simply do not constitute evidence for a claim.

Examples of Bandwagon
Bill says that he likes the idea that people should work for their welfare when they can. His friends laugh at him, accuse him of fascist leanings, and threaten to ostracize him from their group. He decides to recant and abandon his position to avoid rejection.

Bill: "I like classical music and I think it is of higher quality than most modern music."
Jill: "That stuff is for old people."
Dave: "Yeah, only real woosies listen to that crap. Besides, Anthrax rules! It Rules!"
Bill: "Well, I don't really like it that much. Anthrax is much better."

Bill thinks that welfare is needed in some cases. His friends in the Young Republicans taunt him every time he makes his views known. He accepts their views in order to avoid rejection.


Appeal to Pity
An Appeal to Pity is a fallacy in which a person substitutes a claim intended to create pity for evidence in an argument. The form of the "argument" is as follows:

P is presented, with the intent to create pity.
Therefore claim C is true.
This line of "reasoning" is fallacious because pity does not serve as evidence for a claim. This is extremely clear in the following case: "You must accept that 1+1=46, after all I'm dying..." While you may pity me because I am dying, it would hardly make my claim true.

Examples of Appeal to Pity
Jill: "He'd be a terrible coach for the team."
Bill: "He had his heart set on the job, and it would break if he didn't get it."
Jill: "I guess he'll do an adequate job."

"I'm positive that my work will meet your requirements. I really need the job since my grandmother is sick"

"I should receive an 'A' in this class. After all, if I don't get an 'A' I won't get the fellowship that I want."


Logical Imposters
Difficult to spot

Four types of Logical Imposters
1. No-in-betweens (False Dilemma)
2. Slippery Slope
3. Circular reasoning
4. Two wrongs make a right


False Dilemma
A False Dilemma is a fallacy in which a person uses the following pattern of "reasoning":

Either claim X is true or claim Y is true (when X and Y could both be false).
Claim Y is false.
Therefore claim X is true.
This line of "reasoning" is fallacious because if both claims could be false, then it cannot be inferred that one is true because the other is false. That this is the case is made clear by the following example:

Either 1+1=4 or 1+1=12.
It is not the case that 1+1=4.
Therefore 1+1=12.
In cases in which the two options are, in fact, the only two options, this line of reasoning is not fallacious. For example:

Bill is dead or he is alive.
Bill is not dead.
Therefore Bill is alive.

Examples of False Dilemma
Senator Jill: "We'll have to cut education funding this year."
Senator Bill: "Why?"
Senator Jill: "Well, either we cut the social programs or we live with a huge deficit and we can't live with the deficit."

Bill: "Jill and I both support having prayer in public schools."
Jill: "Hey, I never said that!"
Bill: "You're not an atheist are you Jill?"

"Look, you are going to have to make up your mind. Either you decide that you can afford this stereo, or you decide you are going to do without music for a while."


Slippery Slope
The Slippery Slope is a fallacy in which a person asserts that some event must inevitably follow from another without any argument for the inevitability of the event in question. In most cases, there are a series of steps or gradations between one event and the one in question and no reason is given as to why the intervening steps or gradations will simply be bypassed. This "argument" has the following form:

Event X has occurred (or will or might occur).
Therefore event Y will inevitably happen.
This sort of "reasoning" is fallacious because there is no reason to believe that one event must inevitably follow from another without an argument for such a claim. This is especially clear in cases in which there is a significant number of steps or gradations between one event and another.

Examples of Slippery Slope
"We have to stop the tuition increase! The next thing you know, they'll be charging $40,000 a semester!"

"The US shouldn't get involved militarily in other countries. Once the government sends in a few troops, it will then send in thousands to die."

"You can never give anyone a break. If you do, they'll walk all over you."

"We've got to stop them from banning pornography. Once they start banning one form of literature, they will never stop. Next thing you know, they will be burning all the books!"


Circular Reasoning/ Begging the Question
Begging the Question is a fallacy in which the premises include the claim that the conclusion is true or (directly or indirectly) assume that the conclusion is true. This sort of "reasoning" typically has the following form.

Premises in which the truth of the conclusion is claimed or the truth of the conclusion is assumed (either directly or indirectly).
Claim C (the conclusion) is true.
This sort of "reasoning" is fallacious because simply assuming that the conclusion is true (directly or indirectly) in the premises does not constitute evidence for that conclusion. Obviously, simply assuming a claim is true does not serve as evidence for that claim. This is especially clear in particularly blatant cases: "X is true. The evidence for this claim is that X is true."

Some cases of question begging are fairly blatant, while others can be extremely subtle.

Examples of Begging the Question
Bill: "God must exist."
Jill: "How do you know."
Bill: "Because the Bible says so."
Jill: "Why should I believe the Bible?"
Bill: "Because the Bible was written by God."

"If such actions were not illegal, then they would not be prohibited by the law."

"The belief in God is universal. After all, everyone believes in God."

Interviewer: "Your resume looks impressive but I need another reference."
Bill: "Jill can give me a good reference."
Interviewer: "Good. But how do I know that Jill is trustworthy?"
Bill: "Certainly. I can vouch for her."


Two Wrongs Make a Right
Two Wrongs Make a Right is a fallacy in which a person "justifies" an action against a person by asserting that the person would do the same thing to him/her, when the action is not necessary to prevent B from doing X to A. This fallacy has the following pattern of "reasoning":

It is claimed that person B would do X to person A.
It is acceptable for person A to do X to person B (when A's doing X to B is not necessary to prevent B from doing X to A).
This sort of "reasoning" is fallacious because an action that is wrong is wrong even if another person would also do it.

It should be noted that it can be the case that it is not wrong for A to do X to B if X is done to prevent B from doing X to A or if X is done in justified retribution. For example, if Sally is running in the park and Biff tries to attack her, Sally would eb jsutified in attacking Biff to defend herself. As another example, if country A is planning to invade country B in order to enslave the people, then country B would be justified in launching a pre-emptive strike to prevent the invasion.

Examples of Two Wrongs Make a Right
Bill has borrowed Jane's expensive pen, but found he didn't return it. He tell's himself that it is okay to keep it, since she would have taken his.

Jane: "Did you hear about those terrorists killing those poor people? That sort of killing is just wrong."
Sue: "Those terrorists are justified. After all, their land was taken from them. It is morally right for them to do what they do."
Jane: "Even when they blow up busloads of children?"
Sue: "Yes."

After leaving a store, Jill notices that she has underpaid by $10. She decides not to return the money to the store because if she had overpaid, they would not have returned the money.

Jill is horrified by the way the state uses capital punishment. Bill says that capital punishment is fine, since those the state kill don't have any qualms about killing others.


Distorters/ Distracters
Ad Hominem
Red Herring
Straw Man


Ad Hominem
Translated from Latin to English, "Ad Hominem" means "against the man" or "against the person."

An Ad Hominem is a general category of fallacies in which a claim or argument is rejected on the basis of some irrelevant fact about the author of or the person presenting the claim or argument. Typically, this fallacy involves two steps. First, an attack against the character of person making the claim, her circumstances, or her actions is made (or the character, circumstances, or actions of the person reporting the claim). Second, this attack is taken to be evidence against the claim or argument the person in question is making (or presenting). This type of "argument" has the following form:

Person A makes claim X.
Person B makes an attack on person A.
Therefore A's claim is false.
The reason why an Ad Hominem (of any kind) is a fallacy is that the character, circumstances, or actions of a person do not (in most cases) have a bearing on the truth or falsity of the claim being made (or the quality of the argument being made).

Example of Ad Hominem
Bill: "I believe that abortion is morally wrong."
Dave: "Of course you would say that, you're a priest."
Bill: "What about the arguments I gave to support my position?"
Dave: "Those don't count. Like I said, you're a priest, so you have to say that abortion is wrong. Further, you are just a lackey to the Pope, so I can't believe what you say."


Red Herring
A Red Herring is a fallacy in which an irrelevant topic is presented in order to divert attention from the original issue. The basic idea is to "win" an argument by leading attention away from the argument and to another topic. This sort of "reasoning" has the following form:

Topic A is under discussion.
Topic B is introduced under the guise of being relevant to topic A (when topic B is actually not relevant to topic A).
Topic A is abandoned.
This sort of "reasoning" is fallacious because merely changing the topic of discussion hardly counts as an argument against a claim.

Examples of Red Herring
"We admit that this measure is popular. But we also urge you to note that there are so many bond issues on this ballot that the whole thing is getting ridiculous."

"Argument" for a tax cut:
"You know, I've begun to think that there is some merit in the Republican's tax cut plan. I suggest that you come up with something like it, because If we Democrats are going to survive as a party, we have got to show that we are as tough-minded as the Republicans, since that is what the public wants."

"Argument" for making grad school requirements stricter:
"I think there is great merit in making the requirements stricter for the graduate students. I recommend that you support it, too. After all, we are in a budget crisis and we do not want our salaries affected."


Straw Man
The Straw Man fallacy is committed when a person simply ignores a person's actual position and substitutes a distorted, exaggerated or misrepresented version of that position. This sort of "reasoning" has the following pattern:

Person A has position X.
Person B presents position Y (which is a distorted version of X).
Person B attacks position Y.
Therefore X is false/incorrect/flawed.
This sort of "reasoning" is fallacious because attacking a distorted version of a position simply does not constitute an attack on the position itself. One might as well expect an attack on a poor drawing of a person to hurt the person.

Examples of Straw Man
Prof. Jones: "The university just cut our yearly budget by $10,000."
Prof. Smith: "What are we going to do?"
Prof. Brown: "I think we should eliminate one of the teaching assistant positions. That would take care of it."
Prof. Jones: "We could reduce our scheduled raises instead."
Prof. Brown: " I can't understand why you want to bleed us dry like that, Jones."

"Senator Jones says that we should not fund the attack submarine program. I disagree entirely. I can't understand why he wants to leave us defenseless like that."

Bill and Jill are arguing about cleaning out their closets:
Jill: "We should clean out the closets. They are getting a bit messy."
Bill: "Why, we just went through those closets last year. Do we have to clean them out everyday?"
Jill: "I never said anything about cleaning them out every day. You just want too keep all your junk forever, which is just ridiculous."


Inductive Fallacies
Hasty Generalzations
Biased Generalzations
Non Sequitur
Post hoc, ergo propter hoc
Chicken or the egg


Hasty Generalization
This fallacy is committed when a person draws a conclusion about a population based on a sample that is not large enough. It has the following form:

Sample S, which is too small, is taken from population P.
Conclusion C is drawn about Population P based on S.
The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization:

X% of all observed A's are B''s.
Therefore X% of all A's are Bs.
The fallacy is committed when not enough A's are observed to warrant the conclusion. If enough A's are observed then the reasoning is not fallacious.

Small samples will tend to be unrepresentative. As a blatant case, asking one person what she thinks about gun control would clearly not provide an adequate sized sample for determing what Canadians in general think about the issue. The general idea is that small samples are less likely to contain numbers proportional to the whole population. For example, if a bucket contains blue, red, green and orange marbles, then a sample of three marbles cannot possible be representative of the whole population of marbles. As the sample size of marbles increases the more likely it becomes that marbles of each color will be selected in proprtion to their numbers in the whole population. The same holds true for things others than marbles, such as people and their political views.

Since Hasty Generalization is committed when the sample (the observed instances) is too small, it is important to have samples that are large enough when making a generalization. The most reliable way to do this is to take as large a sample as is practical. There are no fixed numbers as to what counts as being large enough. If the population in question is not very diverse (a population of cloned mice, for example) then a very small sample would suffice. If the population is very diverse (people, for example) then a fairly large sample would be needed. The size of the sample also depends on the size of the population. Obviously, a very small population will not support a huge sample. Finally, the required size will depend on the purpose of the sample. If Bill wants to know what Joe and Jane think about gun control, then a sample consisting of Bill and Jane would (obviously) be large enough. If Bill wants to know what most Australians think about gun control, then a sample consisting of Bill and Jane would be far too small.

People often commit Hasty Generalizations because of bias or prejudice. For example, someone who is a sexist might conclude that all women are unfit to fly jet fighters because one woman crashed one. People also commonly commit Hasty Generalizations because of laziness or sloppiness. It is very easy to simply leap to a conclusion and much harder to gather an adequate sample and draw a justified conclusion. Thus, avoiding this fallacy requires minimizing the influence of bias and taking care to select a sample that is large enough.

One final point: a Hasty Generalization, like any fallacy, might have a true conclusion. However, as long as the reasoning is fallacious there is no reason to accept the conclusion based on that reasoning.

Examples of Hasty Generalization
Smith, who is from England, decides to attend graduate school at Ohio State University. He has never been to the US before. The day after he arrives, he is walking back from an orientation session and sees two white (albino) squirrels chasing each other around a tree. In his next letter home, he tells his family that American squirrels are white.

Sam is riding her bike in her home town in Maine, minding her own business. A station wagon comes up behind her and the driver starts beeping his horn and then tries to force her off the road. As he goes by, the driver yells "get on the sidewalk where you belong!" Sam sees that the car has Ohio plates and concludes that all Ohio drivers are jerks.

Bill: "You know, those feminists all hate men."
Joe: "Really?"
Bill: "Yeah. I was in my philosophy class the other day and that Rachel chick gave a presentation."
Joe: "Which Rachel?"
Bill: "You know her. She's the one that runs that feminist group over at the Women's Center. She said that men are all sexist pigs. I asked her why she believed this and she said that her last few boyfriends were real sexist pigs. "
Joe: "That doesn't sound like a good reason to believe that all of us are pigs."
Bill: "That was what I said."
Joe: "What did she say?"
Bill: "She said that she had seen enough of men to know we are all pigs. She obviously hates all men."
Joe: "So you think all feminists are like her?"
Bill: "Sure. They all hate men."


Biased Sample/ Biased Generalizations
This fallacy is committed when a person draws a conclusion about a population based on a sample that is biased or prejudiced in some manner. It has the following form:

Sample S, which is biased, is taken from population P.
Conclusion C is drawn about Population P based on S.
The person committing the fallacy is misusing the following type of reasoning, which is known variously as Inductive Generalization, Generalization, and Statistical Generalization:

X% of all observed A's are B''s.
Therefore X% of all A's are Bs.
The fallacy is committed when the sample of A's is likely to be biased in some manner. A sample is biased or loaded when the method used to take the sample is likely to result in a sample that does not adequately represent the population from which it is drawn.

Biased samples are generally not very reliable. As a blatant case, imagine that a person is taking a sample from a truckload of small colored balls, some of which are metal and some of which are plastic. If he used a magnet to select his sample, then his sample would include a disproportionate number of metal balls (after all, the sample will probably be made up entirely of the metal balls). In this case, any conclusions he might draw about the whole population of balls would be unreliable since he would have few or no plastic balls in the sample.

The general idea is that biased samples are less likely to contain numbers proportional to the whole population. For example, if a person wants to find out what most Americans thought about gun control, a poll taken at an NRA meeting would be a biased sample.

Since the Biased Sample fallacy is committed when the sample (the observed instances) is biased or loaded, it is important to have samples that are not biased making a generalization. The best way to do this is to take samples in ways that avoid bias. There are, in general, three types of samples that are aimed at avoiding bias. The general idea is that these methods (when used properly) will result in a sample that matches the whole population fairly closely. The three types of samples are as follows

Random Sample: This is a sample that is taken in such a way that nothing but chance determines which members of the population are selected for the sample. Ideally, any individual member of the population has the same chance as being selected as any other. This type of sample avoids being biased because a biased sample is one that is taken in such a way that some members of the population have a significantly greater chance of being selected for the sample than other members. Unfortunately, creating an ideal random sample is often very difficult.

Stratified Sample: This is a sample that is taken by using the following steps: 1) The relevant strata (population subgroups) are identified, 2) The number of members in each stratum is determined and 3) A random sample is taken from each stratum in exact proportion to its size. This method is obviously most useful when dealing with stratified populations. For example, a person's income often influences how she votes, so when conducting a presidential poll it would be a good idea to take a stratified sample using economic classes as the basis for determining the strata. This method avoids loaded samples by (ideally) ensuring that each stratum of the population is adequately represented.

Time Lapse Sample: This type of sample is taken by taking a stratified or random sample and then taking at least one more sample with a significant lapse of time between them. After the two samples are taken, they can be compared for changes. This method of sample taking is very important when making predictions. A prediction based on only one sample is likely to be a Hasty Generalization (because the sample is likely to be too small to cover past, present and future populations) or a Biased Sample (because the sample will only include instances from one time period).
People often commit Biased Sample because of bias or prejudice. For example, a person might intentionally or unintentionally seek out people or events that support his bias. As an example, a person who is pushing a particular scientific theory might tend to gather samples that are biased in favor of that theory.

People also commonly commit this fallacy because of laziness or sloppiness. It is very easy to simply take a sample from what happens to be easily available rather than taking the time and effort to generate an adequate sample and draw a justified conclusion.

It is important to keep in mind that bias is relative to the purpose of the sample. For example, if Bill wanted to know what NRA members thought about a gun control law, then taking a sampleat a NRA meeting would not be biased. However, if Bill wanted to determine what Americans in general thought about the law, then a sample taken at an NRA meeting would be biased.

Examples of Biased Sample
Bill is assigned by his editor to determine what most Americans think about a new law that will place a federal tax on all modems and computers purchased. The revenues from the tax will be used to enforce new online decency laws. Bill, being technically inclined, decides to use an email poll. In his poll, 95% of those surveyed opposed the tax. Bill was quite surprised when 65% of all Americans voted for the taxes.

The United Pacifists of America decide to run a poll to determine what Americans think about guns and gun control. Jane is assigned the task of setting up the study. To save mailing costs, she includes the survey form in the group's newsletter mailing. She is very pleased to find out that 95% of those surveyed favor gun control laws and she tells her friends that the vast majority of Americans favor gun control laws.

Large scale polls were taken in Florida, California, and Maine and it was found that an average of 55% of those polled spent at least fourteen days a year near the ocean. So, it can be safely concluded that 55% of all Americans spend at least fourteen days near the ocean each year.


Non Sequitor/ Missing the point
The premises of an argument do support a particular conclusion--but not the conclusion that the arguer actually draws.

Example of Non Sequitor:
"The seriousness of a punishment should match the seriousness of the crime. Right now, the punishment for drunk driving may simply be a fine. But drunk driving is a very serious crime that can kill innocent people. So the death penalty should be the punishment for drunk driving." The argument actually supports several conclusions-- "The punishment for drunk driving should be very serious," in particular--but it doesn't support the claim that the death penalty, specifically, is warranted.

Tip: Separate your premises from your conclusion. Looking at the premises, ask yourself what conclusion an objective person would reach after reading them. Looking at your conclusion, ask yourself what kind of evidence would be required to support such a conclusion, and then see if you've actually given that evidence. Missing the point often occurs when a sweeping or extreme conclusion is being drawn, so be especially careful if you know you're claiming something big.


post hoc, ergo propter hoc
A Post Hoc is a fallacy with the following form:

A occurs before B.
Therefore A is the cause of B.
The Post Hoc fallacy derives its name from the Latin phrase "Post hoc, ergo propter hoc." This has been traditionally interpreted as "After this, therefore because of this." This fallacy is committed when it is concluded that one event causes another simply because the proposed cause occurred before the proposed effect. More formally, the fallacy involves concluding that A causes or caused B because A occurs before B and there is not sufficient evidence to actually warrant such a claim.

It is evident in many cases that the mere fact that A occurs before B in no way indicates a causal relationship. For example, suppose Jill, who is in London, sneezed at the exact same time an earthquake started in California. It would clearly be irrational to arrest Jill for starting a natural disaster, since there is no reason to suspect any causal connection between the two events. While such cases are quite obvious, the Post Hoc fallacy is fairly common because there are cases in which there might be some connection between the events. For example, a person who has her computer crash after she installs a new piece of software would probably suspect that the software was to blame. If she simply concluded that the software caused the crash because it was installed before the crash she would be committing the Post Hoc fallacy. In such cases the fallacy would be committed because the evidence provided fails to justify acceptance of the causal claim. It is even theoretically possible for the fallacy to be committed when A really does cause B, provided that the "evidence" given consists only of the claim that A occured before B. The key to the Post Hoc fallacy is not that there is no causal connection between A and B. It is that adequate evidence has not been provided for a claim that A causes B. Thus, Post Hoc resembles a Hasty Generalization in that it involves making a leap to an unwarranted conclusion. In the case of the Post Hoc fallacy, that leap is to a causal claim instead of a general proposition.

Not surprisingly, many superstitions are probably based on Post Hoc reasoning. For example, suppose a person buys a good luck charm, does well on his exam, and then concludes that the good luck charm caused him to do well. This person would have fallen victim to the Post Hoc fallacy. This is not to say that all "superstitions" have no basis at all. For example, some "folk cures" have actually been found to work.

Post Hoc fallacies are typically committed because people are simply not careful enough when they reason. Leaping to a causal conclusion is always easier and faster than actually investigating the phenomenon. However, such leaps tend to land far from the truth of the matter. Because Post Hoc fallacies are committed by drawing an unjustified causal conclusion, the key to avoiding them is careful investigation. While it is true that causes precede effects (outside of Star Trek, anyways), it is not true that precedence makes something a cause of something else. Because of this, a causal investigation should begin with finding what occurs before the effect in question, but it should not end there.

Examples of Post Hoc
I had been doing pretty poorly this season. Then my girlfriend gave me this neon laces for my spikes and I won my next three races. Those laces must be good luck...if I keep on wearing them I can't help but win!

Bill purchases a new PowerMac and it works fine for months. He then buys and installs a new piece of software. The next time he starts up his Mac, it freezes. Bill concludes that the software must be the cause of the freeze.

Joan is scratched by a cat while visiting her friend. Two days later she comes down with a fever. Joan concludes that the cat's scratch must be the cause of her illness.

The Republicans pass a new tax reform law that benefits wealthly Americans. Shortly thereafter the economy takes a nose dive. The Democrats claim that the the tax reform caused the economic woes and they push to get rid of it.

The picture on Jim's old TV set goes out of focus. Jim goes over and strikes the TV soundly on the side and the picture goes back into focus. Jim tells his friend that hitting the TV fixed it.

Jane gets a rather large wart on her finger. Based on a story her father told her, she cuts a potato in half, rubs it on the wart and then buries it under the light of a full moon. Over the next month her wart shrinks and eventually vanishes. Jane writes her father to tell him how right he was about the cure.


Chicken or the egg (Which one came first?)
Chicken or the egg is base on a situation in which it is difficult to tell which one of two things was the cause of the other. A sentence with no certain for which one of the object come first.

Example of Chicken or the egg:
Chicken was born the eggs.
The eggs born chickens or the chickens born the eggs?

Gangsterism affects the director to make more violence films.
Gangsterism affects the director to make violence films or the violence films influence the social increase gangsterism?

Sources:
Dr. Michael C. Labossiere,
http://www.nizkor.org/features/fallacies/

Hurley, Patrick J. A Concise Introduction to Logic. Thornson Learning, 2000 Lunsford, Andrea and John Ruszkiewicz. Everything's an Argument. Bedford Books, 1998. Copi, Irving M. and Carl Cohen. Introduction to Logic. Prentice Hall, 1998.
http://www.unc.edu/depts/wcweb/handouts/fallacies.html

Our Soul is looks like that
Long time I din find ghost videos. So now I have to post one interesting video to here. Have a nice watch on that "white cloud" moving on the stairs and pass through the wall.

BoA - Winter Love (MIDI)

Yeah....... finally the midi was released. Here is the download link:
BoA - Winter Love (MIDI)

The instrument is listen very nice if you play with Yamaha MidRadio (XG SoftSynthesizer).

For anybody who visited my blog, please visit my homepage also http://www.freewebs.com/junclj

Now I building my homepage (around 80%, still under process and will keep improving)

Midi are suck?
Not all MIDI are suck. Some MIDI are difference from normal MIDI. For example, XG Midi and GS Midi.

XG Midi is composed by YAMAHA
GS Midi is composed by ROLAND

How did a MIDI compose?
Just same like a musician playing their instruments for example playing electric piano, keyboard, electric organ etc plug with computer to compose a MIDI file with some professional software for example "Cakewalk Sonar Producer".


Want to listen your MIDI in different way?
Here have a YAMAHA Midi Player with XG Synthesizer.

YAMAHA MidRadio
Download Here
Sample MIDI

Free Files, Mp3, Image, Videos Hosting (1GB)

eSnips
www.eSnips.com

eSnips Upload Tools

http://www.esnips.com/escentral/client/esnips.exe

Advantages:
- Support resume uploading even disconnected.
- free and easy to use
- login with your email

What is the purpose that I introduce this "eSnips"?
Easier for all people who want to host their files especially who want to share files to their friends and building webpage with mp3s, files, images hosting.

Seoul

I went to Seoul, South Korea at December of 2004. Only got one word can describe about Seoul. It is very "nice" city. Seoul is an advanced city with many tall "mirrors" buildings around the roads. My journey to South Korea was around Christmas and the weather is very cold (around -1~-10 degree Celsius).

The city is quite big, how big? So I can tell you, I still remember that time we depart from our hotel and go to a restaurant for breakfast. We took about 1 hour journey, my GOD all the buidings, bridges and overpasses around us. No traffic jam and still early in the morning in that time, after we took about 1 hour journey to restaurant, there still remain a city... so big (Of course Seoul is metropolis).

Since that time I sit inside a tourist bus, all the mirrors inside the bus was frozen by fog. South Koreans are driving KIA, Hyundai and Ssangyong. They don’t driving Toyota, Nissan, Mitsubishi, Ford, BMW, Volvo etc. Only few of them who are rich, they are driving Mercedes Benz.

The airport is quite far from city, it is Incheon International Airport. Yes…. The airport is quite new and large. Many boeing 747 around that airport. But I am riding MAS Airbus to Seoul.

Oh yes, Seoul have many Japanese tourist. Especially when I go to parks, playground and others travel spot, I always saw Japanese girls. They looks pretty but I wonder know why they wear less than us especially their legs (the weather is very cold please).

I forgot to say, the largest playground in South Korea is Everland. http://www.everland.com The tour leader told us, in South Korea there has a rich businessman who is the Boss of SAMSUNG company. Who was the founder of "Everland". Everyone who will know, SAMSUNG is the largest electronic industry in South Korea.

Last edit here --> when I come back from South Korea. I just know about the news "tsunami" at that time. Indonesian should receive thier retribution after 6 years, the God will punish them after 6 years since 1998 disorders.

Top 18 City Skyline in the World
http://necromanc.blogspot.com/2006/03/top-18-skylines-in-world.html

Which cities I have visited before?
Hong Kong,
Taipei,
Shanghai,
Sydney,
Kuala Lumpur,
Singapore,
Bangkok,
Seoul.

Which cities that I like most?
Singapore, Sydney and Seoul

Which cities that I hope to visit?
Tokyo and Los Angeles

BoA- Key of Heart (Single) (August 2006)
01 Key of Heart (Japanese)
02 Dotch
03 Key of Heart (English)
04 Key of Heart (Korean)

BoA- Winter Love (Single) (2006)
01 Winter Love
02 Candle Lights
03 Last Christmas
04 Winter Love (TV MIX)
05 Candle Lights (TV MIX)

TVXQ - "o"-正.反.合. MV

Tips how to save YouTube Video Clips

This link may helpful for you:
http://javimoya.com/blog/youtube_en.php

BoA - Winter Love MV

TVXQ 東方神起 3rd Album "O" 正.反.合 (Released on 29th Sept)

















01 . "O"-正.反.合
02 . 세상에 단 하나뿐인 마음(You're my miracle)
03 . Hey!Girl
04 . Get me some
05 . I'll be there
06 . Remember
07 . 이제 막 시작된 이야기(The story has just begun)
08 . ON&ON
09 . Phantom 환영(幻影)
10 . You only love
11 . 풍선(Balloons)

Download link:
Full Album
"O"-正.反.合 Japanese Version

My favourite artist?

Hehe..... so now i want to introduce my favourite artist.

<-- She is BoA, and this is her 21st Japanese Single "Winter Love"










For more information, pls visit.

website:
BoAjjang

forum:
BoAjjang Forum