Oct 26th CH 6 Fallacies FALLACY OCCURS WHEN THERE IS NO LOGICAL SUPPORT FOR THE CLAIM Misplacing the Burden of Proof Appeal to ignorance - Saying something is true because it isn’t proven as false Begging the Question (Circular Reasoning) - Worst logical mistake you could make When the premise already assumes that the conclusion is true Ex: The bible says it’s the word of God. The word of God must obviously be true, therefore, whatever the bible says must be true Appeal to emotion - Tied to rhetorical devices Our emotions can be wrong Argument from Outrage - Speaker tries to convince you by there degree of anger Gets you angry, possibly for good reason, and then it says “therefore you should believe this…” Scapegoating - Get people mad, and then say, “and its their fault” Blaming people for problem that makes you angry All you have to do to solve the problem is get rid of the people blamed Ex: “the team is bad because of the coach. To solve the problem, fire the coach” Scare Tactics - Make you afraid, and then say “I will now protect you” People who are afraid let their logical guard down more than angry people Argument from Pity - Makes you feel bad for something Plays on positive emotions of care Argument from Envy Apple Polishing - Ex: “A smart person like you knows that…” Guilt Trips - Make you feel guilty Peer Pressure Argument - Ex: “Everyone knows that…” Ex: “Its common sense that…” Group Think Arguments - Because you are a part of this group you should think this sort of way Nationalism is a powerful part of this Irrelevant Conclusion - Tricky Every fallacy we have done are in some ways an irrelevant conclusion Two wrongs don’t make a right No connection between the claim and the solution Ex: “They are doing the wrong thing, therefore, I should do the same wrong thing” Nov. 1 CH 7: Induction Fallacies - Arguments that are supposed to raise the probability of their conclusions, but are so weak as to fail almost entirely to do so Hasty Generalization - When you generalize from to small a sample The smallest possible sample is the anecdote Argument by Anecdote Scientifically, the amount of people we meet in real life is not a big enough sample to make empirical conclusions Reading books is a way to “live another person’s life” How homogenous is the thing we are generalizing about? The more homogenous, the smaller the sample size we need to make an accurate generalization Humans aren’t very homogenous, so it’s difficult to use small sample size Generalizing from exceptional cases - Is the entity that you are generalizing from unusual? Monkey study: scientists gave monkeys a calorie reduced diet and studied how long they lived, they found that the monkeys lived longer. Concluded that people should eat less. The problem is that the right amount to eat is the amount that keeps you healthy and makes you live longer. The only the scientists found out was that they were overfeeding the monkey. Self-Selection Fallacy - When someone generalizes incautiously from a self-selected sample Generalization from a bias sample - The populations sampled is somehow bias Does not reflect the entire population Difference between this and exceptional question is that even if sample size is increased, bias will still exist Example is a poll: the people who answer the poll are only people who watch that channel, or more generally, people who watch new on television. Even more generally, the poll will only be polling people that like to answer polls. Only accurate poll would be a mandatory poll that randomly selects people to poll. ALL VOLUNTARY POLLS ARE BIASED. In life, we do need to generalize, so we need to make sure we qualify our generalization accurately. “In my experience…, In this case…” The Fallacy of Accident - - The inverse of generalizing When you try to apply a general rule to an incidence to which it doesn’t apply If it’s a fallacy, it’s usually a case where everyone knows it is an exceptional case Ex: you should always return people’s property. If a shooter drops their gun, don’t pick it up and return it to him. Fallacy is problematic for Kantian ethics, because Kantian ethics doesn’t allow for exceptions Another problem is in law. All precedent setting free speech cases in the US limit free speech. (shouting fire in a crowded theatre, causing others harm through your speech), socialist speech was banned at one point. In Canada, free speech in this case was defended, even though we don’t have an absolute right to free speech. Precedent highlights this fallacy Weak analogy A. B. - 1, 2, 3, 4….10 1, 2, 3, 4….? Analogy tries to explain that one thing is like the other because of the similar characteristics More analogues, better analogy The better the analogues relate to the feature, the better the analogy Fewer dis-analogues, the better the analogy Analogies get more complicated in moral arguments (abortion debates) Metaphors and similes are vaguer versions of analogies Appeal to Authority - You should believe this claim because the person making it is a person of authority Involves the credibility question - - Must question if authority figure is actually credible Ex: My son thinks Samsung is better than iPhone, and he should know because he is a teenager Ex: Bob has been doing weather on local weather channel for 20 years. I would take his opinion on global warming over anyone I don’t know Some authorities are credible Appeal to Popularity - When someone treats an issue that cannot be settled by public opinion as if it can Ex: The Iranians have nuclear weapons, everyone knows that Mistaken Appeal to Common Practice/Fallacy from Common Practice - Someone justifies a practice on the grounds that is traditional or is commonly practiced Truth is independent of whether anyone believes it at all Ex: This is the right way; it’s the way it has always been done Argument from Tradition - You should do something because that is how its always been done That’s how your culture does it Cultures change though Bandwagon Fallacy - Mentioning the popularity of something to play on the psychological inducement to believe it Playing on the human tendency to want to belong to a group Ex: Everyone thinks that… Fallacies Related to Cause and Effect - Scientists must worry about these fallacies Science uses the method of agreement to determine the cause of something (things that are in agreement or common) These fallacies can arise because you overlook other possibilities of causation Happen by forgetting about random variation in the world Post Hoc, Ergo Propter Hoc - David Hume recognized this fallacy long ago In the extreme form, we never see causality, simply correlation Assuming causality is an argument to the best inference Underlying all science is a philosophical idea Means “after this, therefore because of it” Assuming that one event coming after another establishes that it was caused by the other. Ex: After I pooped, my cold went away fast. Therefore, pooping caused my cold to go away fast.’ Overlooking the Possibility of Coincidence Overlooking a Possible Common Cause (Ex: I slept with lights on, this caused my headache. Could have common cause like going to bed drunk) - Overlooking the Possibility of Random Variation (ignoring the fact that values of variables fluctuate randomly. Average drive length of group may be different in two different tests) Overlooking the Possibility of Statistical Regression (if the average value of a variable is atypical in one measurement, it is likely to be less atypical on a subsequent measurement); particularly applies to medical research because you are usually starting with a sick person in an unusual state. Giving sick person medicine and they get better in two weeks; they get better, but it may not be because of the medicine. Things tend to return to a mean baseline. Cum Hoc, Ergo Propter Hoc - “With this, therefore because of it” Assuming that two events happening at about the same time establishes that one caused the other. Ex: John had a heart attack while praying, therefore the prayer caused his heart attack Overlooking the Possibility of Coincidence Overlooking a Possible Common Cause Overlooking the Possibility of Reversed Causation (Ex: Successful people drive nice cars, therefore, driving nice cars makes you successful); the causal order goes the other way. Argument by Anecdote Slippery Slope - Argument that rests on an unsupported warning that something will progress by degrees to an undesirable outcome Some slopes are slippery, some are not Because we start down a certain path, we must stay on that certain path; we spent this much money so far so might as well keep spending money on it (slippery slope and false dilemma) Ex: Raising the pentagons budget by 5% this year will result in a 5% increase every year. In 20 years, the whole budget will go to the military. Unstable Explanation/Untestable Claims - Carl Popper: truth claims must be falsifiable. Must be able to be tested to be false. Popper got this idea from Bertrand Russel When someone offers an explanation that could not be tested even in principle Ex: He has heart issues because of sins done in a previous life Line-Drawing Again - Just because you cannot draw a precise line between a weak analogy and one that is not weak, does not mean that every analogy is weak or that none are, or that there is no such thing as the fallacy of weak analogy Subjectivist Fallacy - Things are not made true because you decide or want them to be true Ex: morals are subjective and that’s what I just believe - True subjectivist view is randomly believing something without reasons Belief is something you think is true because of reasons Also relates to aesthetics; subjectivists should like everything so they can enjoy everything Ex: people choose tastes in music with their identity, and they don’t like certain thing because they go against their identity People tend towards subjectivism because of the vast amount of opinions existing, as well as the difficulty of determining which opinion is true Pg 214 #2 Hasty Generalization; generalizing from exceptional cases #3 weak analogy #4 Generalizing from exceptional cases #5 weak analogy #7 Fallacy of accident #16 slippery decision Formal Fallacies - Very strict fallacies of form Less inductive; black and white Argument is 100% wrong Modus Ponens is most basic argument we use. It is a correct argument o If P then Q _______ Q - o Starts with a condition o Ex: “If sherry has her drivers license, sherry can drive her car” o If P then Q. P therefor q o First premise is conditional (If P then Q) o Made into argument with (P therefore Q) o P is antecedent o Q is consequent Affirming the consequent is Modus Ponens gone wrong o If P then Q o Q ______ o P o - - - - - - Ex: If Ghandi was killed in a plane crash, he would be dead. Ghandi is dead, therefore he was killed in a plane crash Denying the antecedent o If P then Q o No P ___ o Not Q Undistributed Middle o Mistaken categorical logic o Categorical logic: logic about categories or classes of things o Part of our cognitive logic is to map the world out into categories of things 1. All sharks are fish 2. All salmon are fish 3. All sharks are salmon o Middle term is fish 1. If she passed the course, she is very bright 2. If she did well on the final, she is very bright 3. Therefore, if she did well on the final, she passed the course o She is very bright is the middle term Equivocation o When a word used in the premise is used in a different way in the conclusion o Shift in the meaning allows person making an argument to have a shift in accepting a claim different than initially argued o Ex: Some triangles are obtuse. Whatever is obtuse is ignorant. Therefore, some triangles are ignorant. Fallacy of amphiboly o Usually comes from punctuation o Missing commas o Lots of bad puns use this o Ex: Mr. Wilson said he went out on the balcony to watch the fireworks in his pajamas. We can conclude he must have spent the evening in the hospital. o Ex: you must show a birth certificate and a drivers license or a passport to apply to the program. Fallacy of Division o Applying characteristics of the whole to the parts o Just because it’s the top team in the league doesn’t mean it is the top player Fallacy of Composition o What is true of the individual isn’t true of the group o Ex: just because you have the top players in the team doesn’t mean you are the top team in the league - - - Confusing explanations of excuses o Explanation of how something occurs doesn’t have moral content o Naturalistic Fallacy: Descriptive statement: says what is Normative statement: has implicit or explicit should Descriptive statements cannot make moral claims o Explanations are descriptive statement and can’t give us moral claim o Ex: There are gay animals. This descriptive claim does not have any moral implications Confusing contraries and contradictories o Contradictory claims have opposite truth value. If one is true, the other is false. o Contrary claims have quality that in one case they can’t both be true and in the other case they can’t be false Ex: Some animals are cats and some animals are not cats Consistent claims can be all true at the same time, and inconsistent claims cannot be all true at the same time Miscalculating Probability o Gambler’s Fallacy If you flip a coin that lands on heads 10 times, it still has a 50% chance of landing on heads on the eleventh time Fallacy occurs when you think things are causally related when they are not o Overlooking prior probabilities When there might be a causal relationship you haven’t deduced, and you are assessing probability without necessary facts Ex: Hal has a better chance at becoming a pro hockey player then bill does of becoming a pro rugby player. Hal is the better athlete. Pg. 236 Bible question: fallacy of division Mothers eyes: amphiboly Cranberry Beer: fallacy of composition MT #2 6-9 Categorical Logic - Type of deductive logic Our minds like to sort things into different classes or categories Ex: all sharks are fish Categories also apply to predicates Predicate can function to distinguish a subclass of a category of things Argument o If you are under the age of 18, you are a minor o If you are a minor, you cannot be sued o If you are under 18, you cannot be sued - Four types of categorical claims 1. (A) ALL___ are ____ wolves/mammals a. All of one class are a part of another call 2. (E) NO ____ are ____ lizards/mammals a. A and E are universal claims; talk about all members of group 3. (I) SOME ___ are ____ mammals/sea creatures 4. (o) SOME ____ are not ____ mammals/sea creatures a. I and O are particular claim - Terms that mark their range are quantifiers - First thing is subject, second is predicate - Affirmative: something is something - Negative: something isn’t something - Categorical is single propositional claim - First break down claim to simplest form - “only” is a universal categorical operator - Ex: Only sophomores are eligible candidates - Only applies to predicate - All eligible candidates are sophomores - Only X are Y means all Y are X - If word “the” happens before “only” means it introduces the subject. - Look for terms specifying total inclusion or exclusion - Mass nouns are terms for which there is no “one” of them o Ex: air, water - To deal with this, you must do “all examples of mass noun are predicate” - For persons, the problem is uniqueness - Ex: “all individuals identical with__ are ____” - Same problem with anything unique, like art - Ex: “all works identical with__ are___” Pg. 251 #2 some lizards are not salamanders #3 all lizards are reptiles #5 all thingys are snakes #6 no snakes are poisonous #12 all people who arrived are cheerleaders A and E cannot both be true I and O cannot both be false Conversion - Only applies to E and I No A are B, it means nor B are A All cats are animal does not mean all animals are cats Obversion Propositional Logic - - Deductive logic Reducing entire proposition into a letter Operators are logical connectors between proposition Generally uppercase Ps or Qs; as long as you have a key, u can use any letter Reducing complex sentences, sentences with more than one proposition, into simple claims Ex: “logic is simple”- L “Logic is not simple”- ̴L & or (.) means and v means or if/then is o first term is sufficient o Second erm is necessary (PvQ) & ̴ (P&Q) for exclusive “or” The general “or” is inclusive A & B v C is ambiguous Adding a comma: A & B, v C makes it (A & B) v T Adding a comma: A, & B v C makes it A & (B v C) If paula doesn’t go to work, then quincy will have to work o ̴PQ If there is a line were they are both true then they are consistent claims Monus Ponens (MP) Modus Tollens (MT) o If P then Q o Not Q then not P Disjunctive Argument 1. P v Q 2. ̴P Q 1. P v Q 2. ̴Q P Chain Argument 1. PQ 2. QR 3. RS PS Simplification 1. P&Q P Conjunction 1. P 2. Q P&Q Addition 1. P 2. P v Q Constructive Dilemma 1. (PQ) & (RS) 2. P v R QvS Destructive Dilemma 1. (PQ) & (RS) 2. ̴Q v ̴S _______________________ ̴P v ̴R *first fourteen rules are what we need to know Equivalencies Double Negations 1. ̴ ̴ P = P Commutation 1. L v B 2. ̴ L 3. B 1. L v B 2. ̴ B 3. L Implication (P Q) = ( P ̴ v Q) Composition (PQ) = ( ̴Q ̴P) Demorgens ̴ (P & Q) = ( P ̴ v Q ̴ ) CH 11 (generalizations and analogies) CH 12?
