No, I have not read that one. It looks good. I think cognitve biases and logical fallacies are the cornorstones to "magical thinking". (I appreciate your recent cites and posts on such.) And magical interpretations -- whether of experiences, "scriptures" or current events.
Magical thinking (MT) takes one to the opposite cornor of What Is. MT may bring some feel-good comfort to the soul, and be the fuel for dreamers, but ultimately its illusion and delusion. In my reading / interpretation (we all make interpretations) of various hindu-related scriptures, a sharp intellect and the ability to finely discriminate are cited valuable tools in uncovering what is real and what is unreal. Discrimination of what is Real and Unreal. Discrimination between Buddhi and Purusha and all. Knowing the existence and structure of cognitve biases and logical fallacies, being able to readily indentify them and avoid them are part of that sharpening process. --- In FairfieldLife@yahoogroups.com, "curtisdeltablues" <[EMAIL PROTECTED]> wrote: > > Excellent post. Are you hip to Gilovitch's book: How We Know What > isn't So, The fallibility of human reason in everyday life? He studies > human cognitive error at Cornell. > > http://www.amazon.com/gp/product/0029117062/sr=8-1/qid=1149893839/ref=pd_bbs_1/102-4458199-6191348?%5Fencoding=UTF8 > > > --- In FairfieldLife@yahoogroups.com, new_morning_blank_slate > <no_reply@> wrote: > > > > We all make them. To the extent that we are aware of their existence > > and structure, we can avoid them in our own internal reasoning, and in > > communications. > > > > Whoever has more than 20 in any post, gets a gallon of woowoo juice. > > > > > > http://en.wikipedia.org/wiki/List_of_cognitive_biases > > > > Cognitive bias is distortion in the way we perceive reality (see also > > cognitive distortion). > > > > Some of these have been verified empirically in the field of > > psychology, others are considered general categories of bias. > > > > This is an incomplete list, which may never be able to satisfy > > certain standards for completeness. > > > > > > > > Decision making and behavioral biases > > > > Many of these biases are studied for how they affect belief formation > > and business decisions and scientific research > > > > * Bandwagon effect - the tendency to do (or believe) things > > because many other people do (or believe) the same. > > * Bias blind spot - the tendency not to compensate for one's own > > cognitive biases. > > * Choice-supportive bias - the tendency to remember one's choices > > as better than they actually were. > > * Confirmation bias - the tendency to search for or interpret > > information in a way that confirms one's preconceptions. > > * Congruence bias - the tendency to test hypotheses exclusively > > through direct testing > > * Contrast effect - the enhancement or diminishment of a weight or > > other measurement when compared with recently observed contrasting > object. > > * Disconfirmation bias - the tendency for people to extend > > critical scrutiny to information which contradicts their prior beliefs > > and accept uncritically information that is congruent with their prior > > beliefs. > > * Endowment effect - the tendency for people to value something > > more as soon as they own it. > > * Focusing effect - prediction bias occurring when people place > > too much importance on one aspect of an event; causes error in > > accurately predicting the utility of a future outcome. > > * Hyperbolic discounting - the tendency for people to have a > > stronger preference for more immediate payoffs relative to later > > payoffs, the closer to the present both payoffs are. > > * Illusion of control - the tendency for human beings to believe > > they can control or at least influence outcomes which they clearly > cannot. > > * Impact bias - the tendency for people to overestimate the length > > or the intensity of the impact of future feeling states. > > * Information bias - the tendency to seek information even when it > > cannot affect action > > * Loss aversion - the tendency for people to strongly prefer > > avoiding losses over acquiring gains (see also sunk cost effects) > > * Neglect of Probability - the tendency to completely disregard > > probability when making a decision under uncertainty. > > * Mere exposure effect - the tendency for people to express undue > > liking for things merely because they are familiar with them. > > * Color psychology - the tendency for cultural symbolism of > > certain colors to affect affective reasoning. > > * Omission Bias - The tendency to judge harmful actions as worse, > > or less moral than equally harmful omissions (inactions.) > > * Outcome Bias - the tendency to judge a decision by its eventual > > outcome instead of based on the quality of the decision at the time it > > was made. > > * Planning fallacy - the tendency to underestimate task-completion > > times. > > * Post-purchase rationalization - the tendency to persuade oneself > > through rational argument that a purchase was good value. > > * Pseudocertainty effect - the tendency to make risk-averse > > choices if the expected outcome is positive, but risk-seeking choices > > to avoid negative outcomes. > > * Rosy retrospection - the tendency to rate past events more > > positively than they had actually rated them when the event occurred. > > * Selective perception - the tendency for expectations to affect > > perception. > > * Status quo bias - the tendency for people to like things to stay > > relatively the same. > > * Von Restorff effect - the tendency for an item that "stands out > > like a sore thumb" to be more likely to be remembered than other items. > > * Zeigarnik effect - the tendency for people to remember > > uncompleted or interrupted tasks better than completed ones. > > * Zero-risk bias - preference for reducing a small risk to zero > > over a greater reduction in a larger risk. > > > > > > Biases in probability and belief > > > > Many of these biases are often studied for how they affect business > > and economic decisions and how they affect experimental research. > > > > * Affective forecasting > > Affective forecasting is the forecasting of one's affect (emotional > > state) in the future. This kind of prediction is affected by various > > kinds of cognitive biases, i.e. systematic errors of thought. Daniel > > Gilbert of the department of social psychology at Harvard University > > and other researchers in the field, such as Timothy Wilson of the > > University of Virginia and George Loewenstein of Carnegie Mellon > > University, have studied those cognitive biases and given them names > > like "empathy gap" and "impact bias" and the like. > > > > Affective forecasting is an important concept in psychology, because > > psychologists try to study what situations in life are important to > > humans, and how they change their views with time. > > > > > > * Ambiguity effect - the avoidance of options for which missing > > information makes the probability seem "unknown" > > > > The ambiguity effect is a cognitive bias where decision-making is > > affected due to a lack of information, or an "ambiguity." > > > > For example, picture an urn with 90 balls inside of it. The balls are > > colored red, black and yellow. 30 of the balls are red, and the other > > 60 are some combination of black and yellow balls, with all > > combinations being equally likely. In option X, drawing a red ball > > would earn you the $100, and in option Y, drawing a black ball would > > earn you the $100. The difference between the two options is that the > > number of red balls is certain for option X, but the number of black > > balls for option Y is uncertain. > > > > Which option gives you the best chance at picking out a winning ball? > > The truth is that the probability of picking a winning ball is > > identical for both options X and Y. In option X, where the number of > > red balls is certain, the probability of selecting a winning ball is > > 1/3 (30 red balls out of 90 total balls). In option Y, despite the > > fact that the number of black balls is not certain, the probability of > > selecting a winning ball is also 1/3. This is because the range of > > possibilities as to the number of black balls is some amount between 0 > > and 60. This means that the probability of there being more than 30 > > black balls is the same as there being less than 30 black balls. > > Because of this, according to what is known as the expected-utility > > theory, one should be indifferent between the two options. As a > > result, the chances of winning the $100 are the same for both urns. > > > > People are much more likely to want to select a ball under option X, > > where the probability of selecting a winning ball is, in their minds, > > more certain. The question as to the number of black balls under > > scenario Y turns people off to that option. Despite the fact that > > there could possibly be double the black balls to red balls, people > > tend to not want to take the opposing risk that there may be less than > > 30 black balls. The "ambiguity" behind option Y makes people want to > > select option X, even when they are theoretically equivalent. > > > > This bias was discovered by Daniel Ellsberg in 1961. Ellsberg deemed > > these situations where the "probability is unknown" as "ambiguous," > > hence the "ambiguity effect." > > > > One explanation of the effect is that people follow a heuristic, a > > rule of thumb, of avoiding options about what information is missing > > (Frisch & Baron, 1988; Ritov & Baron, 1990). This is usually a good > > rule because it leads us to look for the information. In many cases, > > though, the information cannot be obtained. Information is almost > > always missing, and the effect is often the result of calling some > > particular missing piece to our attention. > > > > * Anchoring - the tendency to rely too heavily, or "anchor," on > > one trait or piece of information when making decisions > > > > * Anthropic bias - the tendency for one's evidence to be biased by > > observation selection effects > > * Attentional bias - neglect of relevant data when making > > judgments of a correlation or association > > * Availability error - the distortion of one's perceptions of > > reality, due to the tendency to remember one alternative outcome of a > > situation much more easily than another > > * Belief bias - the tendency to base assessments on personal > > beliefs (see also belief perseverance and Experimenter's regress) > > * Belief Overkill - the tendency to bring beliefs and values > > together so that they all point to the same conclusion > > * Clustering illusion - the tendency to see patterns where > > actually none exist > > * Conjunction fallacy - the tendency to assume that specific > > conditions are more probable than general ones > > * Gambler's fallacy - the tendency to assume that individual > > random events are influenced by previous random events "the coin has > > a memory" > > * Hindsight bias - sometimes called the "I-knew-it-all-along" > > effect, the inclination to see past events as being predictable > > * Illusory correlation - beliefs that inaccurately suppose a > > relationship between a certain type of action and an effect > > * Myside bias - the tendency for people to fail to look for or to > > ignore evidence against what they already favor > > * Neglect of prior base rates effect - the tendency to fail to > > incorporate prior known probabilities which are pertinent to the > > decision at hand > > * Observer-expectancy effect - when a researcher expects a given > > result and therefore unconsciously manipulates an experiment or > > misinterprets data in order to find it. (see also subject-expectancy > > effect) > > * Overconfidence effect - the tendency to overestimate one's own > > abilities > > * Polarization effect - increase in strength of belief on both > > sides of an issue after presentation of neutral or mixed evidence, > > resulting from biased assimilation of the evidence. > > * Positive outcome bias (prediction) - a tendency in prediction to > > overestimate the probability of good things happening to them. (see > > also wishful thinking and valence effect) > > * Recency effect - the tendency to weigh recent events more than > > earlier events (see also peak-end rule) > > * Primacy effect - the tendency to weigh initial events more than > > subsequent events > > * Subadditivity effect - the tendency to judge probability of the > > whole to be less than the probabilities of the parts. > > > > > > > > Social biases > > > > Most of these biases are labeled as attributional biases. > > > > * Barnum effect (or Forer Effect) - the tendency to give high > > accuracy ratings to descriptions of their personality that supposedly > > are tailored specifically for them, but are in fact vague and general > > enough to apply to a wide range of people. > > * Egocentric bias - occurs when people claim more responsibility > > for themselves for the results of a joint action than an outside > > observer would. > > * False consensus effect - the tendency for people to overestimate > > the degree to which others agree with them. > > * Fundamental attribution error - the tendency for people to > > over-emphasize personality-based explanations for behaviors observed > > in others while under-emphasizing the role and power of situational > > influences on the same behavior. (see also group attribution error, > > positivity effect, and negativity effect) > > * Halo effect - the tendency for a person's positive or negative > > traits to "spill over" from one area of their personality to another > > in others' perceptions of them. (see also physical attractiveness > > stereotype) > > * Illusion of asymmetic insight - people perceive their knowledge > > of their peers to surpass their peers' knowledge of them. > > * Ingroup bias - preferential treatment people give to whom they > > perceive to be members of their own groups. > > * Just-world phenomenon - the tendency for people to believe the > > world is "just" and so therefore people "get what they deserve." > > * Lake Wobegon effect - the human tendency to report flattering > > beliefs about oneself and believe that one is above average (see also > > worse-than-average effect, and overconfidence effect). > > * Notational bias - a form of cultural bias in which a notation > > induces the appearance of a nonexistent natural law. > > * Outgroup homogeneity bias - individuals see members of their own > > group as being relatively more varied than members of other groups. > > * Projection bias - the tendency to unconsciously assume that > > others share the same or similar thoughts, beliefs, values, or > positions. > > * Self-serving bias - the tendency to claim more responsibility > > for successes than failures. It may also manifest itself as a tendency > > for people to evaluate ambiguous information in a way beneficial to > > their interests. (see also group-serving bias) > > * Trait ascription bias - the tendency for people to view > > themselves as relatively variable in terms of personality, behavior > > and mood while viewing others as much more predictable. > > * Self-fulfilling prophecy - the tendency to engage in behaviors > > that elicit results which will (consciously or subconsciously) confirm > > our beliefs. > > > > ========== > > > > Other Cognitive Biases > > > > http://en.wikipedia.org/wiki/Category:Cognitive_biases > > (Some duplicates with above) > > > > * Adaptive Bias > > Adaptive Bias is the idea that the human brain has evolved to reason > > adaptively, rather than truthfully or even rationally, and that > > Cognitive bias may have evolved as a mechanism to reduce the overall > > cost of cognitive errors as opposed to merely reducing the number of > > cognitive errors, when faced with making a decision under conditions > > of uncertainty. > > > > When making decisions under conditions of uncertainty, two kinds of > > errors need to be taken into account - "false positives", i.e. > > deciding that a risk or benefit exists when it does not, and "false > > negatives", i.e. failing to notice a risk or benefit that exists. > > False positives are also commonly called "Type 1 errors", and false > > negatives are called "Type 2 errors". > > > > Where the cost or impact of a type 1 error is much greater than the > > cost of a type 2 error (e.g. the water is safe to drink), it can be > > worthwhile to bias the decision making system towards making fewer > > type 1 errors, i.e. making it less likely to conclude that a > > particular situation exists. This by definition would also increase > > the number of type 2 errors. Conversely, where a false positive is > > much less costly than a false negative (blood tests, smoke detectors), > > it makes sense to bias the system towards maximising the probablility > > that a particular (very costly) situation will be recognised, even if > > this often leads to the (relatively un-costly) event of noticing > > something that is not actually there. > > > > Martie G. Haselton and David M. Buss (2003) state that Cognitive Bias > > can be expected to have developed in humans for cognitive tasks where: > > > > * Decision making is complicated by a significant signal-detection > > problem (i.e. when there is uncertainty) > > * The solution to the particular kind of decision making problem > > has had a recurrent effect on survival and fitness throughout > > evolutionary history > > * The costs of a "false positive" or "false negative" error > > dramatically outweighs the cost of the alternative type of error > > > > > > * Affective forecasting > > Affective forecasting is the forecasting of one's affect (emotional > > state) in the future. This kind of prediction is affected by various > > kinds of cognitive biases, i.e. systematic errors of thought. Daniel > > Gilbert of the department of social psychology at Harvard University > > and other researchers in the field, such as Timothy Wilson of the > > University of Virginia and George Loewenstein of Carnegie Mellon > > University, have studied those cognitive biases and given them names > > like "empathy gap" and "impact bias" and the like. > > > > Affective forecasting is an important concept in psychology, because > > psychologists try to study what situations in life are important to > > humans, and how they change their views with time. > > > > * Anchor (NLP) > > * Anthropic bias > > * Apophenia > > * Appeal to pity > > * Attributional bias > > * Availability error > > * Availability heuristic > > > > B > > > > * Base rate fallacy > > * Belief Overkill > > * Bias blind spot > > > > C > > > > * Choice blindness > > * Choice-supportive bias > > * Clustering illusion > > * Confirmation bias > > * Conjunction fallacy > > * Contrast effect > > * Cultural bias > > > > D > > > > * Data dredging > > * Disconfirmation bias > > > > E > > > > * Egocentric bias > > * Empathy gap > > * Endowment effect > > * Errors in Syllogisms > > > > > > E cont. > > > > * Exposure effect > > > > F > > > > * False consensus effect > > * Forer effect > > * Fundamental attribution error > > > > G > > > > * Gambler's fallacy > > * Group attribution error > > * Group-serving bias > > * Groupthink > > > > H > > > > * Halo effect > > * Hindsight bias > > * Hostile media effect > > * Hyperbolic discounting > > > > I > > > > * Illusion of control > > * Impact bias > > * Ingroup bias > > > > J > > > > * Just-world phenomenon > > > > K > > > > * Kuleshov Effect > > > > L > > > > * Lake Wobegon effect > > * Loss aversion > > > > M > > > > * Memory bias > > * Mindset > > * Misinformation effect > > > > N > > > > * Negativity effect > > * Neglect of Probability > > * Notational bias > > > > O > > > > * Observer-expectancy effect > > * Omission Bias > > * Outgroup homogeneity bias > > * Overconfidence effect > > > > P > > > > * Pareidolia > > > > > > P cont. > > > > * Peak-end rule > > * Physical attractiveness stereotype > > * Picture superiority effect > > * Planning fallacy > > * Pollyanna principle > > * Positivity effect > > * Primacy effect > > * Publication bias > > > > R > > > > * Recall bias > > * Recency effect > > * Regression fallacy > > * Response bias > > * Rosy retrospection > > > > S > > > > * Selective perception > > * Self-deception > > * Self-serving bias > > * Serial position effect > > * Spacing effect > > * Status quo bias > > * Subject-expectancy effect > > * Sunk cost > > * Superstition > > * Suspension of judgment > > > > T > > > > * Trait ascription bias > > > > V > > > > * Valence effect > > * Von Restorff effect > > > > W > > > > * Wishful thinking > > * Worse-than-average effect > > > > Z > > > > * Zeigarnik effect > > * Zero-risk bias > > > > > > Memory biases may either enhance or impair the recall of memory, or > > they may alter the content of what we report remembering. > > > > List of memory biases > > > > * Choice-supportive bias - states that chosen options are > > remembered as better than rejected options (Mather, Shafir & Johnson, > > 2000). > > * Classroom effect - states that some portion of student > > performance is explained by the classroom environment and teacher as > > opposed to purely individual factors. > > * Context effect - states that cognition and memory are dependent > > on context, such that out-of-context memories are more difficult to > > retrieve than in-context memories (i.e, recall time and accuracy for a > > work-related memory will be lower at home, and vice versa). > > * Hindsight bias - sometimes called the "I-knew-it-all-along" > > effect, is the inclination to see past events as being predictable. > > * Humor effect - states that humorous items are more easily > > remembered than non-humorous ones, which might be explained by the > > distinctiveness of humor, the increased cognitive processing time to > > understand the humor, or the emotional arousal caused by the humor. > > * Infantile amnesia - states that few memories are retained from > > before age 2. > > * Generation effect - states that self-generated information is > > remembered best. > > * Lag effect > > * Levels-of-processing effect - states that different methods of > > encoding information into memory have different levels of > > effectiveness (Craik & Lockhart, 1972). > > * List-length effect > > * Mere exposure effect - states that familiarity increases liking. > > * Misinformation effect - states that misinformation affects > > people's reports of their own memory. > > * Modality effect - states that memory recall is higher for the > > last items of a list when the list items were received auditorily > > versus visually. > > * Mood congruent memory bias - states that information congruent > > with one's current mood is remembered best. > > * Next-in-line effect > > * Part-list cueing effect - states that being shown some items > > from a list makes it harder to retrieve the other items. > > * Picture superiority effect - states that concepts are much more > > likely to be remembered experimentally if they are presented as > > pictures rather than as words. > > * Positivity effect - states that older adults favor positive over > > negative information in their memories. > > * Processing difficulty effect - see Levels-of-processing effect. > > * Primacy effect - states that the first items on a list show an > > advantage in memory. > > * Recency effect - states that the last items on a list show an > > advantage in memory. > > * Rosy retrospection - states that the past is remembered as > > better than it really was. > > * Serial position effect - states that items at the beginning of a > > list are the easiest to recall, followed by the items near the end of > > a list; items in the middle are the least likely to be remembered. > > * Self-generation effect - states that people are better able to > > recall memories of statements that they have generated than similar > > statements generated by others. > > * Self-relevance effect - states that memories considered > > self-relevent are better recalled that other, similar information > > * Spacing effect - states that while you are more likely to > > remember material if exposed to it many times, you will be much more > > likely to remember it if the exposures are repeated over a longer span > > of time. > > * Suffix effect - states that there is considerable impairment of > > the Recency effect, if a redundant suffix item is added to a list, > > which the subject is not required to recall (Morton, Crowder & > > Prussin, 1972). > > * Testing effect - states that frequent testing of material that > > has been committed to memory improves memory recall more than simply > > study of the material without testing. > > * Time-of-day effect > > * Verbatim effect - states that the "gist" of what someone has > > said is better remembered than the verbatim wording (Poppenk, Walia, > > Joanisse, Danckert, & Köhler, 2006) > > * Von Restorff effect - states that an item that "stands out like > > a sore thumb" is more likely to be remembered than other items (von > > Restorff, 1933). > > * Zeigarnik effect - states that people remember uncompleted or > > interrupted tasks better than completed ones. > > > > > > Recall bias > > From Wikipedia, the free encyclopedia > > Jump to: navigation, search > > > > Taken generally, recall bias is a type of statistical bias which > > occurs when the way a survey respondent answers a question is affected > > not just by the correct answer, but also by the respondent's memory. > > [1] [2] This can affect the results of the survey. As a hypothetical > > example, suppose that a survey in 2005 asked respondents whether they > > believed that O. J. Simpson had killed his wife. Respondents who > > believed him innocent might be more likely to have forgotten about the > > case, and therefore to state no opinion, than respondents who thought > > him guilty. If this is the case, then the survey would find a > > higher-than-accurate proportion of people who believed that O.J. did > > kill his wife. > > > > Relatedly but distinctly, the term might also be used to describe an > > instance where a survey respondent intentionally responds incorrectly > > to a question about their personal history which results in response > > bias. As a hypothetical example, suppose that a researcher conducts a > > survey among women of group A, asking whether they have had an > > abortion, and the same survey among women of group B. > > > > If the results are different between the two groups, it might be that > > women of one group are less likely to have had an abortion, or it > > might simply be that women of one group who have had abortions are > > less likely to admit to it. If the latter is the case, then this would > > skew the survey results; this is a kind of response bias. (It is also > > possible that both are the case: women of one group are less likely to > > have had abortions, and women of one group who have had abortions are > > less likely to admit to it. This would still affect the survey > > statistics.) > > > > ==== > > > > > > Logical Fallacies > > > > Aristotelian fallacies > > [edit] > > > > Material fallacies > > > > The classification of material fallacies widely adopted by modern > > logicians and based on that of Aristotle, Organon (Sophistici > > elenchi), is as follows: > > > > * Fallacy of Accident (also called destroying the exception or a > > dicto simpliciter ad dictum secundum quid) meaning to argue > > erroneously from a general rule to a particular case, without proper > > regard to particular conditions that vitiate the application of the > > general rule; e.g. if manhood suffrage be the law, arguing that a > > criminal or a lunatic must, therefore, have a vote. > > > > * Converse Fallacy of Accident (also called reverse accident, > > destroying the exception, or a dicto secundum quid ad dictum > > simpliciter) meaning to argue from a special case to a general rule. > > > > * Irrelevant Conclusion (also called Ignoratio Elenchi), wherein, > > instead of proving the fact in dispute, the arguer seeks to gain his > > point by diverting attention to some extraneous fact (as in the legal > > story of "No case. Abuse the plaintiff's attorney"). The fallacies are > > common in platform oratory, in which the speaker obscures the real > > issue by appealing to his audience on the grounds of > > o purely personal considerations (argumentum ad hominem) > > o popular sentiment (argumentum ad populum, appeal to the > > majority) > > o fear (argumentum ad baculum) > > o conventional propriety (argumentum ad verecundiam) > > > > This fallacy has been illustrated by ethical or theological > > arguments wherein the fear of punishment is subtly substituted for > > abstract right as the sanction of moral obligation. > > > > * Begging the question (also called Petitio Principii or Circulus > > in Probando--arguing in a circle) consists in demonstrating a > > conclusion by means of premises that pre-suppose that conclusion. > > Jeremy Bentham points out that this fallacy may lurk in a single word, > > especially in an epithet, e.g. if a measure were condemned simply on > > the ground that it is alleged to be "un-English". > > > > * Fallacy of the Consequent, really a species of Irrelevant > > Conclusion, wherein a conclusion is drawn from premises that do not > > really support it. > > > > * Fallacy of False Cause, or Non Sequitur (L., it does not > > follow), wherein one thing is incorrectly assumed as the cause of > > another, as when the ancients attributed a public calamity to a > > meteorological phenomenon (a special case of this fallacy also goes by > > the Latin term post hoc ergo propter hoc; the fallacy of believing > > that temporal succession implies a causal relation). > > > > * Fallacy of Many Questions (Plurium Interrogationum), wherein > > several questions are improperly grouped in the form of one, and a > > direct categorical answer is demanded, e.g. if a prosecuting counsel > > asked the prisoner " What time was it when you met this man? " with > > the intention of eliciting the tacit admission that such a meeting had > > taken place. Another example is the classic line, "Is it true that you > > no longer beat your wife?" > > > > [edit] > > > > Verbal fallacies > > > > Verbal fallacies are those in which a false conclusion is obtained by > > improper or ambiguous use of words. They are generally classified as > > follows. > > > > * Equivocation consists in employing the same word in two or more > > senses, e.g. in a syllogism, the middle term being used in one sense > > in the major and another in the minor premise, so that in fact there > > are four not three terms ("All fair things are honourable; This woman > > is fair; therefore this woman is honourable," the second "fair" being > > in reference to complexion). > > * Amphibology is the result of ambiguity of grammatical structure, > > e.g. of the position of the adverb "only" in careless writers ("He > > only said that," in which sentence, as experience shows, the adverb > > has been intended to qualify any one of the other three words). > > * Fallacy of Composition is a species of Amphibology that results > > from the confused use of collective terms. e.g. "The angles of a > > triangle are less than two right angles" might refer to the angles > > separately or added together. > > * Division, the converse of the preceding, which consists in > > employing the middle term distributively in the minor and collectively > > in the major premise. > > * Accent, which occurs only in speaking and consists of > > emphasizing the wrong word in a sentence. e.g., "He is a fairly good > > pianist," according to the emphasis on the words, may imply praise of > > a beginner's progress, or an expert's depreciation of a popular hero, > > or it may imply that the person in question is a deplorable violinist. > > * Figure of Speech, the confusion between the metaphorical and > > ordinary uses of a word or phrase. > > > > Logical Fallacies > > > > http://en.wikipedia.org/wiki/Fallacy > > > > The standard Aristotelian logical fallacies are: > > > > * Fallacy of Four Terms (Quaternio terminorum) > > * Fallacy of Undistributed Middle > > * Fallacy of Illicit process of the major or the Illicit minor term; > > * Fallacy of Negative Premises. > > > > [edit] > > > > Other systems of classification > > > > Of other classifications of fallacies in general the most famous are > > those of Francis Bacon and J. S. Mill. Bacon (Novum Organum, Aph. 33, > > 38 sqq.) divided fallacies into four Idola (Idols, i.e. False > > Appearances), which summarize the various kinds of mistakes to which > > the human intellect is prone. With these should be compared the > > Offendicula of Roger Bacon, contained in the Opus maius, pt. i. J. S. > > Mill discussed the subject in book v. of his Logic, and Jeremy > > Bentham's Book of Fallacies (1824) contains valuable remarks. See Rd. > > Whateley's Logic, bk. v.; A. de Morgan, Formal Logic (1847) ; A. > > Sidgwick, Fallacies (1883) and other textbooks. > > [edit] > > > > Fallacies in the media and politics > > > > Fallacies are used frequently by pundits in the media and politics. > > When one politician says to another, "You don't have the moral > > authority to say X", this could be an example of the argumentum ad > > hominem or personal attack fallacy; that is, attempting to disprove X, > > not by addressing validity of X but by attacking the person who > > asserted X. Arguably, the politician is not even attempting to make an > > argument against X, but is instead offering a moral rebuke against the > > interlocutor. For instance, if X is the assertion: > > > > The military uniform is a symbol of national strength and honor. > > > > Then ostensibly, the politician is not trying to prove the contrary > > assertion. If this is the case, then there is no logically fallacious > > argument, but merely a personal opinion about moral worth. Thus > > identifying logical fallacies may be difficult and dependent upon > context. > > > > In the opposite direction is the fallacy of argument from authority. A > > classic example is the ipse dixit"He himself said it" argumentused > > throughout the Middle Ages in reference to Aristotle. A modern > > instance is "celebrity spokespersons" in advertisements: a product is > > good and you should buy/use/support it because your favorite celebrity > > endorses it. > > > > An appeal to authority is always a logical fallacy, though it can be > > an appropriate form of rational argument if, for example, it is an > > appeal to expert testimony. In this case, the expert witness must be > > recognized as such and all parties must agree that the testimony is > > appropriate to the circumstances. This form of argument is common in > > legal situations. > > > > By definition, arguments with logical fallacies are invalid, but they > > can often be (re)written in such a way that they fit a valid argument > > form. The challenge to the interlocutor is, of course, to discover the > > false premise, i.e. the premise that makes the argument unsound. > > [edit] > > > > General list of fallacies > > > > The entries in the following list are neither exhaustive nor mutually > > exclusive; that is, several distinct entries may refer to the same > > pattern. As noted in the introduction, these fallacies describe > > erroneous or at least suspect patterns of argument in general, not > > necessarily argument based on formal logic. Many of the fallacies > > listed are traditionally recognized and discussed in works on critical > > thinking; others are more specialized. > > > > * Ad hominem (also called argumentum ad hominem or personal > > attack) including: > > o ad hominem abusive (also called argumentum ad personam) > > o ad hominem circumstantial (also called ad hominem > > circumstantiae) > > o ad hominem tu quoque (also called you-too argument) > > * Amphibology (also called amphiboly) > > * Appeal to authority (also called argumentum ad verecundiam or > > argument by authority) > > * Appeal to emotion including: > > o Appeal to consequences (also called argumentum ad > > consequentiam) > > o Appeal to fear (also called argumentum ad metum or > > argumentum in terrorem) > > o Appeal to flattery > > o Appeal to pity (also called argumentum ad misericordiam) > > o Appeal to ridicule > > o Appeal to spite (also called argumentum ad odium) > > o Two wrongs make a right > > o Wishful thinking > > * Appeal to the majority (also called Appeal to belief, Argumentum > > ad numerum, Appeal to popularity, Appeal to the people, Bandwagon > > fallacy, Argumentum ad populum, Authority of the many, Consensus > > gentium, Argument by consensus) > > * Appeal to motive > > * Appeal to novelty (also called argumentum ad novitatem) > > * Appeal to probability > > * Appeal to tradition (also called argumentum ad antiquitatem or > > appeal to common practice) > > * Argument from fallacy (also called argumentum ad logicam) > > * Argument from ignorance (also called argumentum ad ignorantiam > > or argument by lack of imagination) > > * Argument from silence (also called argumentum ex silentio) > > * Appeal to force (also called argumentum ad baculum) > > * Appeal to wealth (also called argumentum ad crumenam) > > * Appeal to poverty (also called argumentum ad lazarum) > > * Argument from repetition (also called argumentum ad nauseam) > > * Base rate fallacy > > * Begging the question (also called petitio principii, circular > > argument or circular reasoning) > > * Conjunction fallacy > > * Continuum fallacy (also called fallacy of the beard) > > * Correlative based fallacies including: > > o Fallacy of many questions (also called complex question, > > fallacy of presupposition, loaded question or plurium interrogationum) > > o False dilemma (also called false dichotomy or bifurcation) > > o Denying the correlative > > o Suppressed correlative > > * Definist fallacy > > * Dicto simpliciter, including: > > o Accident (also called a dicto simpliciter ad dictum > > secundum quid) > > o Converse accident (also called a dicto secundum quid ad > > dictum simpliciter) > > * Equivocation > > * Engineering Fallacy > > * Fallacies of distribution: > > o Composition > > o Division > > o Ecological fallacy > > * Fallacies of Presumption > > * False analogy > > * False premise > > * False compromise > > * Faulty generalization including: > > o Biased sample > > o Hasty generalization (also called fallacy of insufficient > > statistics, fallacy of insufficient sample, fallacy of the lonely > > fact, leaping to a conclusion, hasty induction, secundum quid) > > o Overwhelming exception > > o Statistical special pleading > > * Gambler's fallacy/Inverse gambler's fallacy > > * Genetic fallacy > > * Guilt by association > > * Historian's fallacy > > * Homunculus fallacy > > * If-by-whiskey (argues both sides) > > * Ignoratio elenchi (also called irrelevant conclusion) > > * Inappropriate interpretations or applications of statistics > > including: > > o Biased sample > > o Correlation implies causation > > o Gambler's fallacy > > o Prosecutor's fallacy > > o Screening test fallacy > > * Incomplete comparison > > * Inconsistent comparison > > * Invalid proof > > * Judgemental language > > * Juxtaposition > > * Lump of labour fallacy (also called the fallacy of labour > scarcity) > > * Meaningless statement > > * Middle ground (also called argumentum ad temperantiam) > > * Misleading vividness > > * Naturalistic fallacy > > * Negative proof > > * Non sequitur including: > > o Affirming the consequent > > o Denying the antecedent > > * No true Scotsman > > * Package deal fallacy > > * Perfect solution fallacy > > * Poisoning the well > > * Progressive fallacy ("New is improved") > > * Proof by assertion > > * Questionable cause (also called non causa pro causa) including: > > o Correlation implies causation (also called cum hoc ergo > > propter hoc) > > o Fallacy of the single cause > > o Joint effect > > o Post hoc (also called post hoc ergo propter hoc) > > o Regression fallacy > > o Texas sharpshooter fallacy > > o Wrong direction > > * Red herring (also called irrelevant conclusion) > > * Reification (also called hypostatization) > > * Relativist fallacy (also called subjectivist fallacy) > > * Retrospective determinism (it happened so it was bound to) > > * Shifting the burden of proof > > * Slippery slope > > * Special pleading > > * Straw man > > * Style over substance fallacy > > * Sunk cost fallacy > > * Syllogistic fallacies, including: > > o Affirming a disjunct > > o Affirmative conclusion from a negative premise > > o Existential fallacy > > o Fallacy of exclusive premises > > o Fallacy of four terms (also called quaternio terminorum) > > o Fallacy of the undistributed middle > > o Illicit major > > o Illicit minor > > > > [edit] > > > > General examples > > > > Fallacious arguments involve not only formal logic but also causality. > > Others involve psychological ploys such as use of power relationships > > between proposer and interlocutor, appeals to patriotism and morality, > > appeals to ego etc., to establish necessary intermediate (explicit or > > implicit) premises for an argument. Indeed, fallacies very often lay > > in unstated assumptions or implied premises in arguments that are not > > always obvious at first glance. One way to obscure a premise is > > through enthymeme. > > > > We now give a few examples illustrating common errors in reasoning. > > Note that providing a critique of an argument has no relation to the > > truth of the conclusion. The conclusion could very well be true, while > > the argument itself is not valid. See argument from fallacy. > > > > In the following, we view an argument as a dialogue between a proposer > > and an interlocutor. > > [edit] > > > > Example 1: Material Fallacy > > > > James argues: > > > > 1. Cheese is food. > > 2. Food is delicious. > > 3. Therefore, cheese is delicious. > > > > This argument claims to prove that cheese is delicious. This > > particular argument has the form of a categorical syllogism. Any > > argument must have premises as well as a conclusion. In this case we > > need to ask what the premises are, that is the set of assumptions the > > proposer of the argument can expect the interlocutor to grant. The > > first assumption is almost true by definition: cheese is a foodstuff > > edible by humans. The second assumption is less clear as to its > > meaning. Since the assertion has no quantifiers of any kind, it could > > mean any one of the following: > > > > * All food is delicious. > > * Most food is delicious. > > * All food is delicious, except for spoiled or moldy food. > > * Some food is disgusting. > > > > In any of the last three interpretations, the above syllogism would > > then fail to have validated its second premise. James may try to > > assume that his interlocutor believes that all food is delicious; if > > the interlocutor grants this then the argument is valid. In this case, > > the interlocutor is essentially conceding the point to James. However, > > the interlocutor is more likely to believe that some food is > > disgusting, such as a sheep's liver white chocolate torte; and in this > > case James is not much better off than he was before he formulated the > > argument, since he now has to prove the assertion that cheese is a > > unique type of universally delicious food, which is a disguised form > > of the original thesis. From the point of view of the interlocutor, > > James commits the logical fallacy of begging the question. > > [edit] > > > > Example 2: Verbal Fallacy > > > > Barbara argues: > > > > 1. Andre is a good tennis player. > > 2. Therefore, Andre is 'good', that is to say a morally good person. > > > > Here the problem is that the word good has different meanings, which > > is to say that it is an ambiguous word. In the premise, Barbara says > > that Andre is good at some particular activity, in this case tennis. > > In the conclusion, she says that Andre is a morally good person. These > > are clearly two different senses of the word "good". The premise might > > be true but the conclusion can still be false: Andre might be the best > > tennis player in the world but a rotten person morally. However, it is > > not legitimate to infer he is a bad person on the ground there has > > been a fallacious argument on the part of Barbara. Nothing concerning > > Andre's moral qualities is to be inferred from the premise. > > Appropriately, since it plays on an ambiguity, this sort of fallacy is > > called the fallacy of equivocation, that is, equating two incompatible > > terms or claims. > > [edit] > > > > Example 3: Verbal Fallacy > > > > Ramesh argues: > > > > 1. Nothing is better than eternal happiness. > > 2. Eating a hamburger is better than nothing. > > 3. Therefore, eating a hamburger is better than eternal happiness. > > > > This argument has the appearance of an inference that applies > > transitivity of the two-placed relation is better than, which in this > > critique we grant is a valid property. The argument is an example of > > syntactic ambiguity. In fact, the first premise semantically does not > > predicate an attribute of the subject, as would for instance the > assertion > > > > A potato is better than eternal happiness. > > > > In fact it is semantically equivalent to the following universal > > quantification: > > > > Everything fails to be better than eternal happiness. > > > > So instantiating this fact with eating a hamburger, it logically > > follows that > > > > Eating a hamburger fails to be better than eternal happiness. > > > > Note that the premise A hamburger is better than nothing does not > > provide anything to this argument. This fact really means something > > such as > > > > Eating a hamburger is better than eating nothing at all. > > > > Thus this is a fallacy of composition. > > [edit] > > > > Example 4: Logical Fallacy > > > > In the strictest sense, a logical fallacy is the incorrect application > > of a valid logical principle or an application of a nonexistent > principle: > > > > 1. Some drivers are men. > > 2. Some drivers are women. > > 3. Therefore, some drivers are both men and women. > > > > This is fallacious. Indeed, there is no logical principle that states > > > > 1. For some x, P(x). > > 2. For some x, Q(x). > > 3. Therefore for some x, P(x) and Q(x). > > > > An easy way to show the above inference is invalid is by using Venn > > diagrams. In logical parlance, the inference is invalid, since under > > at least one interpretation of the predicates it is not validity > > preserving. > > > ------------------------ Yahoo! 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