Week 1 How to Argue and ReasonDefinition of an argument a series of sentences, statements or propositions where some of the premises are conclusions where the premises are intended to give a reason for the conclusionWhat are they used for to change belief (persuasion) is used to convince can justify but not always persuade to give a reason for belief (justification) the goal of the argument may be different than the resultsQuestions to ask is the arguer trying to change my mind if yes then it is a persuasive argument is the arguer trying to give some kind of reason for belief if yes then it is justification strong argument don’t always persuadeWhat else are they used for explanation: is giving a reason why something happened goal is to increase understanding why it is trueAristotle’s 4 forms of explanations causal teleological: the why or the goal formal: why it is true material Example: Train Whistle Causal: conductor pulls the lever Teleological: he wanted to warn traffic Formal: the construction of the whistle and how it works Material: The density of the air make the soundArgument Explanation general principles or laws initial conditions therefore phenomenon to be explained goal is to fit into general pattern explanation: an attempt to fit a particular phenomenon into a general pattern in order toincrease understanding and remove bewilderment or surprise1.6 what are they made of sentences, statements, propositions = language language is: important, conventional, representational and social important because it is necessary for life as we know it conventional: most people follow the rules depending on what the rules are for thatculture. example football and soccer

representational: cannot change the facts of the world Social: must be used conventionally to get what you want from others Semantic, physical production, structural combination, etiquette pronunciation: we are not always aware of the rule and do not have to be to follow it1.7 meaning concerned with linguistic meaning what words mean are what they refer to sentences are facts this is the referential / descriptive view and is not accurate what would the word hello represent under this view? Meaning is use and is a conjunction so it is not an objectLinguistic act Meaningful utteranceSpeech Act advice?Conversational used to bring an effect1.8(optional) Linguistic acts utter a set of words that follow semantics and syntax songs could be meaningful utterance must be grammatical must make senseGarden path sentences the man who whistles tunes pianos Buffalo buffalo Buffalo1.9 speech acts (optional) saying makes it so the thereby tests: if I say, I ___, then I thereby ____ words can change the world If I say I apologize then I thereby apologizeCircumstances matter if I say “I ___” in the appropriate circumstances then I thereby ___ thanking, promises, apologizing Arguing is a speech act1.10 (optional) Conversational acts to bring about a change in the world EFFECT example: asking to borrow a car conversational act is the bringing about of the intended effect for the kind of speech actthat the speaker is performing does not occur when the effect does not occur example shooting and killingConversational Maxims Quantity Don’t say too much or too little give the right amount of infomation

Quality Don’t lie or say something that you don’t believe Relevance Manner orderly brief avoid obscurity avoid ambiguity Used if cooperatingArgue Conversational implication is not logical implication is false if it logically entails something that is false

Week 2 how to ArgueArgument makers certain words indicate that some sentences are the reason for others

switching the order does make a difference in this case So, therefore, thus, hence, accordingly are argument markers Conclusion markers: the sentence after the marker is the conclusionPremise (reason marker) reason is after the word because for as for the reason since since is not always a marker use one of the other markers to test the meaningIf may seem like an argument marker but is not on its own antecedence (if one thing) consequent (then another) is not counted as an argument marker2.2 Standard form premise then lines (reson) then the conclusion or therefore symbol number the reasons2.3 A problem for arguments the premise(s) must support conclusion an argument cannot justify you in believing that the conclusion is true unless you arejustified in believing that the premises are true if an argument is required to justify a premise then your are in “skeptical regress”Ways to avoid the Regress1. start with premis that is unjustifiablea. since it cannot be justified it leads to false beliefs2. use an argument with a circular regressa. Premise cannot be a conclusion3. use an infinite chain of argumentsa. premise must have independent justificationReal ways to solve regress problem in everyday life start with assumptions that everyone shares assure the audience discount objections or gaurd claim find shared assumption2.4 Assuring if a reason is not given then it cannot be questionedAuthoritative (assurance) cites authority relies on the trust in the sourceReflective selfassurancesurety feelingsAbusive

belittle the opponent conditional abuse if you don’t agree with them appeal to common senseBenefits saves time avoids the regressDownfall poor authority distraction dropping and acting as if its trueNot appropriate when no one would question the claim authority not trustworthy you have enough time2.5 Guarding make premise weaker and harder to object to use personal beliefs lessen the degree on continuumProbability lowering in certainty depends on expectationsMental based on personal beliefs it may be considered rude to question how someone feels2.6 discounting citing the objection but as an indication of which is more important but before emphasizes clause although is before the de emphasized clauseThe trick of discounting straw people the pick 5 easy objections to counter to distract and leave the rest unaddressed2.7 Evaluation preference is not to be confused with evaluation good meet the standards avoids the setting of specific standards so avoid the regress we don’t have to agree on the stands (exp why to turn left) people can apply their own standards to the situation some words are abstract (general) good bad right wrong Some words are specific beautiful ugly cruel kindContextual liberal vs conservative depends on the party is not evaluative

Combining negatives and positives depends on the meaningToo can take a neutral and make it a negativeSlanting use of evaluative without giving reasons used in weak arguments2.8 close analysis mark a passage underline and place codes for the purpose the word serves rhetorical ge the reader to come up with reasons of their own

Week 3 how to argue3.1 ValidityVices one or more premise is false the premise do not provide good cause or relation between premises and conclusionDeductive Argument

conclusion should follow from the premises is supposed to be validValid if and only if its not possible for the premise to be true and the conclusion to be false try to tell coherent story to test whenever the conclusion is false one of the premises must be falseWhat valid is not valid does not mean good does not depend on whether the premise is true or false focuses on possibilityKinds of ArgumentsTrue premise true conclusion (valid) to be valid there can be no way for either one to be falses and the other trueTrue premise true conclusion (not valid) if there is a way for (possibility) the conclusion not to be true then it will not be trueFalse premise true conclusion can be validTrue premise false conclusion cannot be valid3.2 Soundness all premises are true so conclusion must be true soundness must have true premises and must be valid must have true premise , conclusion and validity3.3 Get down to basicsReconstruction goal of reconstruction is to put an argument in a form in which we can easily andaccurately assess it in as fair a manner as possibleSteps1. close analysis2. remove excess words or verbiage3. put in standard form4. clarify premises5. divid into subarguments6. asses where each arguments validity7. add suppressed premises8. check each premise for truth9. qualify premise to make them true10. concludeRoad Markers (excess verbiage) helpful to keep track of an argument be not anything else saying what the argument or topic will be aboutTangent (type of verbiage) unrelated to issue irrelevant may keep attention or interest

can be used as a distraction or red herringTrick of excess verbiage guarding ters can make hard to determine this3.4 Sharpen edges (clarify) seek adequate precision and clarity but not absolute pick the most charitable option or interpretationBreak up the premises if it doesn't add confusion cannot make it look bad the word and can be broken up the word or cannotOrganise parts can build on argument on top of each other in chain linear structureLinear structure one premise giving a reason for conclusion which is then a reason for anotherconclusionBranching Each premise by itself would be enough for conclusion provide independent supportJoint two premises work togetherMethod identify and number when they work together put r draw arrow from reason to conclusion rearrange if needed3.6 fill in gaps valid if it is not possible that the premises are true when the conclusion is false if found not to be valid then ad suppressed premises /reason to fill inReason to fill in to examine and assess the assumptions of the argument better to understand the argument betterGoals find the arguers reasoning find any misstepsTypes of suppression factual moral norm based linguistics

Week 4 how to Argue4.1 Deductive arguments are presented as being valid an argument is valid just in case there is no possible way for its premises to be truewhen its conclusion is false not valid if the premises are true and the conclusion false if the premises are true then the conclusions must be trueQuantifiers (only, at least, some, all, none) the use of these make arguments valid

4.2 Propositional Logic ConnectivesProposition a proposition is something that can be either true or false, and that can be the premise ofthe conclusion of an argument.Propositional connective a propositional connective is something that takes propositions and makes newpropositions out of them “and” is sometimes one4.3 “And” and the truthfunctionalconnectivesJack and Jill example join two names to make a complex name makes a complex proposition includes the two people jack talked jill talked Two people talking to each other“and” as a propositional connective can be used to convey temporal meaning or ordering when it is not temporal it is a truthfunctionalconnectiveTruthfunctionalconnective a truth functional connective is a propositional connective that males a new propositionwhose truth or falsity depends solely on the truth or falsity of its propositional ingredients4.4 Truth tables4.5 Disjunction “or” exclusive: may mean one or the other (only one can win) Inclusive: can mean one or the other or both? any situation in which the disjunction is true then it is valid Introductions4.6 Joining of conjunction and disjunction conjunction and disjunction are not associative order changes meaning4.7 negation and truth functional operatorOperators does not connect coverts example: I believe that a truth functional operator is a propositional operator that creates propositions whosetruth depends solely on the truth of the proposition to which the operator is appliedNegation make the premise the opposite of the original truthvalueis the opposite not, it is not the case that

if the pthennegation p if pthenthe negation p+4.8 Negation conjunctions and disjunctions together with conjunction different meaning is true when both or one conjunct are false disjunction either one of the disjuncts could be false false whenever either of one of the disjunct is true4.9 The conditional if… then… is a propositional connectiveRule Modus Ponens from the premise P if P then Q infer QRule Modus Tollens from the premise Q if P then Q infer PConditional the use of the conditional if the argument P C is valid then the conditional if P then C istrue4.10 Conditionals in ordinary language if we use “if then” in the conventional sense or as a proposition if it depends on things other than the truth or falsity cannot be subjunctive “only if” is the same as “if then”4.11 Biconditionals is a propositional connective the larger proposition is true if the two propositions have thesame truth value

How to Argue Week 5Categorical Logic (5.1) no notesCategories and Quantifiers (5.2) The quantifiers make the categories more specific the right quantifier may make the argument valid use venn diagramHow quantifiers modify categories (5.3) A: all F’s are G’s E: no F’s are G’s

I: some F’s are G’s O: some F’s are not G’sImmediate Categorical Inferences (5.4) it is an inferences with just 1 premise, in which both the premise and the conclusion areof the form A,E,I or OSubject term & Predicate Term is the one modified by the quantifier the one that we’ve been schematizing with “F”. theother term is the predicate termConversion The most common example of immediate categorical inferences in which the conclusionswitches the subject and predicate term that occur in the premise Valid for E and I but not A or OSyllogisms (5.5) IS AN ARGUMENT WITH 2 PREMISES AND A CONCLUSION WHERE ALL 3PREPOSITIONS ARE OF THE a,e,i OR o FORM the subject term of the conclusion is called the subject term of the syllogism, and one ofthe premises must also contain that subject term; the premise is the minor premise (not modified) The predicate term of the conclusion is called the predicate term of thesyllogism , and one of the premises must also contain the predicate term; that premise isthe “major premise” 3 categories can use venn diagramIndividuals and language (5.6) Venn diagrams and validity (5.7) Other ways of expressing AEIO(5.8) reasoning from Venn diagrams and truth tables alone (5.9). no notes

How to Argue week 6Inductive arguments (6.1) Types: inferences to the best explanation arguments from analogy statistical generalization statistical application causal reasoning probability decision making

Inductive vs DeductiveDeductive bad when invalid are intended to be valid standard is valid vs invalid all or nothing indefeasible no matter what premise and it will still be validInductive can be good when they are not valid standard is weak or strong strength in degrees not intended to be valid context and determine the strength is defeasible additional information or premises may weaken the argumentGeneralization from sampling (6.2) cannot test everyone Universal the first F is G the Second F is G the rest of the Fs are Gs therefore all Fs are Gs Partial x% of Fs are Gs all x% are Gs inductive arguments of this type do not try to be validWhen are generalizations strong (6.3) sample of chocolate chip cookies example you could lieQuestions to ask1. are the premise false or unjustified (lie)2. to small of sample size ( 1 cookie)a. Fallacy of hasty generalizationb. needed sample size will depend on the type of sample taken apples vsparachutes3. Fallacy of biased samplinga. if you tell them beforehandb. poor people without phones Roosevelt election4. Is the question slanteda. animal research question wordingb. limited optionsc. way it is reportedApplying generalizations (6.4) applying generalization

example: almost never ex: 80% failApplication x% of fs are gs a is f therefore a is probably g they are defeasible premises must be true and justifiable application strength varies with percentagesReference Class may point to different conclusions look at the smallest references class but may make for too small of class/sample they can conflictInference to the best explanation (6.5) justify: reason to believe conclusion is true explanation: something that we know is true but took for granted (natural phenomenon) inferences used in mysteries and scienceExplanation premise explains the conclusion the conclusion describes the phenomenon to be explained and its true.Inferences work in the opposite direction as explanations the conclusion is what does the explaining probably true not always valid but could be good defeasibleWhich explanation is best must be conservative must be falsifiable must not be shallow depends on principle that is not explained but needs explanation must not be Ad Hoc not powerful or broadInference to the best explanation (6.7) strength may differ from person to personArguments from analogy (6.8)Analogy is a comparisonPrecedence use with small cases Object A has properties P Q R object BCD have property X therefore object A probably also has property X

A= subject BCD = the analogous objects PQR= similarities X= the targetIs strong when the similarities are more important there are more similarities there are fewer dissimilarities the analogous objects are more diverse the conclusion is weaker? Make the arguments look as good as possible (how to determine which to use)

Week 7 How to Argue (Causal Reasoning)Causal Reasoning causal judgements cannot be certain inductive arguments are needed to support causal claims general rule or principle help to guide the reasoningGeneral principles Sufficient condition when one occurs so does the other Example: being a whale is sufficient for being a mammal Necessary one cannot be without the other example: being a whale is necessary for being a sperm whaleDefinition Sufficient F is sufficient condition for G= for events; whenever an event F happens an event G also happens

For features;anything that has feature F also has feature G Necessary F is a necessary condition for G= for events:whenever event F does not happen, an event G also does nothappen for features; anything that does not have feature F also does not havefeature GCausal Example striking the match is sufficient for lighting it striking this match on a surface is necessary for lighting it you are always saying it will hold within “normal circumstances” must quantify with “in normal circumstances”Revised Definition F is a sufficient condition for G= in normal circumstances for events whenever an event F happens, an event G slo happens for features; anything that has feature F also has feature G F is a necessary condition for G in normal circumstances for events: whenever event F does not happen an event G also does not happen for features: anything that does not have feature F also has does not have featureGKinds of conditions conceptual causal moral (more controversial)7.2 Negative condition test X is not a sufficient condition of Y if there is any case where X is present and Y is absent detectives use this example: diner chicken not sufficient for death only what is not sufficient7.3 Positive sufficient condition we have a good reason to believe X is a sufficient condition of Y if all of the following aremeta. we have not found any case where X is present and Y is absentb. we have tested a wide variety of cases including cases where x is present andcases where y is absentc. if there are any other features that are never present where Y is absent then wehave tested enough where those other features are absent but X is presentd. we have tested enough cases of various kinds that are likely to induce a casewhere X is present and Y is absent if there is any such case7.4 Negative Necessary condition Tests X is not a necessary condition of Y if there is any case where X is absent and Y ispresent7.5 Positive necessary condition test we have a good reason to believe X is a necessary condition of Y if all of the following

conditions are met we have not found any case where X is absent and Y is present we have tested a wide variety of cases including cases where X is absent and where y ispresent if there are any other features that are never absent where Y is present, then we havetested cases where those other features are present but X is absent we have tested enough cases of various kinds that are likely to include a case where X isabsent and y is present if there is any such case7.6 complex condition both necessary and sufficient7.7 Correlation vs causation the necessary condition test will not workMetone or concomitant variation Aka correlation X and Y are positively correlated when the degree of x increases as the degree of y increases the degree of x decreases as the degree of y decreases X and Y are negatively correlated when the degree of x increases as the degree of y decreases the degree of X decreases as the degree of Y increasesCausal Relations A causes B B causes A Some third thing C causes both A and B Could be coincidentalWays of determining relation temporal : which comes first Manipulation or experimentation7.8 Common fallacies confusing correlation with causation post hoc ergo proptes hoc = after this therefore because of this confusing a cause with effect example bad golf swing and bad back backwards relation

How to Argue Week 88.1Inductive

Statistical generalization from a sample Application of the generalization inference to the best explanation argument from analogy positive sufficient necessary condition test comitant variation

Inductive strength is strong in proportion to probability

Probability cannot tell what is not likely to happen or will not happen examples 7s (gamblers fallacy) the odds are always the same

Representative heuristic the more you see something the more likely you will think it will be Example: three door problem

What is probability 8.2 Terminology

Probability: the number of time that it might happen out of the number of times it occurs example 3/10 equals a .3 probability the range from 0-1 1 means it is certain it will happen 0 means it will not happen

Kinds of probability A priori

You figure it out before hand (assumption) example heads or tails assumes likelihood of alternatives

Statistical or empirical evidence you have to experiment

Probability of negation (8.3)1. Rules

1.1. the probability that an event will NOT occur is 1 - the probability that it will occur

Rule for the probability of conjunction (8.4)1. two events are independent if and only if the occurrence of one has no effect on the

probability of the other.a. example cards

Rule for independent events 1. if two events are independent then the probability that both events will occur in that order

is the product of the probability of the first event time the probability of the second event

Rule for Dependent value The conditional probability of X given Y is the percentage of cases where X occurs out of

the cases where Y occurs the probability of both of two events occurring is the product of probability the first event

occurring time the conditional probability of the second event occurring given that the first event occurred

Rule for probability disjunction (one or the other) (8.5) mutually exclusive the probability that both of them will occur together is 0

the probability of one or the other will occur is the sum of the probability of one and the other

Permutation ordered example coin toss (.5+.5)-.25=.75 combination

Rules for Probabilities Series (8.6) Example Contraceptive two methods:

a. Look at the failure rate and multiply both failure rate Formal rule

the probability that an event will occur at least once in a series of independent trials is 1-the probability that it will not occur in that series.

1-Pr(~h)^nBayes Theorem honors (8.7) Optional

all tests have errors formula to find how accurate the formula is Look at base rate = percentage of those who have condition Look at sensitivity= percentage of those who have condition and test positive look at specificity= percentage of those without the condition that test negative solution or posterior probability= that you tested positive on the test if you have the

condition Box Method

divide the population into four groups (--),(-+)(+,+)(+,-) those who do have the condition/ the total number of those who test positive. hits true positive, False positive, false negative, true negative

Expected financial value (8.8) probability to make decision

Decisions with certainty you know what will happen The chooser knows the actual outcomes of each opinion or alternative action rather than

just the probability of the outcomesDecision under risks

the chooser does not know the actual outcomes of each option or alternative action but does know the probabilities of the outcomes

Most decision fall under this category Expected value theory (8.8 & 8.9)

The expected monetary or financial value of a choice = the probability of winning times the net gain in money of winning minus the probability of losing times the net loss in money of losing.

Lotto winning - the cost of the ticketDiminishing Marginal utility

each increment decreases in value as you get more and more increments example are 10 hamburgers better than 1

Overall value actual overall value of utility of an act = all the good and bad effects that the act actually

hasDecisions with ignorance or uncertainty

the chooser does not know the actual outcomes of the options or alternative actions also does not know even the probabilities of those outcomes

Week 9 Lecture 9.1 introduction to fallacies

kind of bad argument the premises do not support the conclusion whether they are true or false example men who make less than 30k are violent criminals one does not support the

other. not all bad arguments are fallacies

Lecture 9.2 Argument from the heap aka sorites Vagueness

creates fallacies

Principle of mathematical induction (is correct ) the number 0 belongs to F if x belongs to F then x+1 belongs to F

therefore all natural numbers belong to F poor pennies (example)

is a paradox Paradox

the argument and premises are correct the conclusion is not correct even if they premises are true

Lecture 9.3 vagueness An expression is vagueness when there is no precise boundary between the cases to

which is correctly applies and the cases to which it does not Why it leads to paradox

if there is no precise boundaries between cases of correct applications and incorrect applications, then it will seem obviously true that miniscule difference from a particular thing will not change whether or not we have a case of correct or incorrect application. But the problem is that a series of minuscule differences can amount to a large change.

Lecture 9.4 Conceptual slippery slope fallacy is an argument that exploits the vagueness of the category to argue that there is no

significant difference between things that belong to a category and things that do not. premises don’t support the conclusion

Lecture 9.5 Fairness slippery slope Is an argument that exploit the vagueness of a category to agur that it is unfair to treat

cases that fall into that category different from cases that don’t fall into that category Example passing exam 99.99% vs 99.98% vs 99.97% down to 0.01% Assumes that a line cannot be drawn

Lecture 9.6 Causal slippery slope is one that exploits the vagueness of a category to argue that a particular event that

you are considering will lead to a calamity that is causal connected to that event that is connected to that event by a series of steps.

domino effect parade of horrors

Example human euthanasia doctors will start killing everyone Example if you date then you will get married if you get married you will get divorced if

you get divorced then you will not speak to each other so if you date you will eventually end up not speaking to each other.

9.7 Ambiguity There maybe more than one meaning to a word sentence could mean more than one thing example: she is an Asian historian Why ambiguity: if an expression has two acceptable interpretations, and we switch

between those two interpretation in the course of single argument, then we can construct an argument that seems valid even if though it isn’t.

9.8 Semantic and syntactic ambiguity

Semantic: is when a particular word has two different interpretation example: stoned= killed or high

Syntactic: is when you have a phrase that can be given to different interpretation. Grammer.

differ in how you are supposed to understand them.9.9 Fallacies of Equivocation

Is a fallacy that results when an argument seems to be valid only because it switches between two different interpretations of an ambiguous expression.

example: no woman can be rational

Week 10 how to argue 10.1 Fallacies of relevance and vacuity

Fallacies of vagueness are hard to avoid fallacies of relevance and vacuity are easier to avoid it is important for language to have vagueness in it example when are you going to jamaica Example the white house said does the white house talk

Fallacies of Relevance is a fallacy that results when an argument’s premise are not relevant to its conclusion

appeal to authority appeal to popular opinion

Vacuity when you can’t be justified in accepting the premises unless you are independently

justified in accepting the conclusion circularity begging the question

10.2 Fallacy of relevance Ad Hominem one that begins with premises about a particular person who is making an argument,

and ends with a conclusion critical of that person’s argument looks at the motivations of the person as a way to ignore the argument

3 kinds of Ad Hominem

silencer: ends with conclusion we should disregard that persons argument. they

are not entitled to speak on the issue denine that the person as the right to speak

Dismisser: end with the conclusion that the person’s conclusion is fine but thier reasons are not good

Denier Ends with denial of the persons conclusion

10.3 Silencers not all ad hominem are fallacies definition of silencers: begins with premises about a particular person, who is making

a point and ends with a conclusion that we should disregard the person’s argument altogether.

not a fallacy: occur in special cases where there are a lot rules and regulations Argument: I saw the accused murder the victim, Therefore the accused is guilty

of the crime (burst in uninvited and unannounced) the person’s argument might be sound but should be silenced because

there is no way to know its sound violates criminal procedures

Is a fallacy Don’t listen to them they are criminals or weird

10.4 Dismissers Definition: Begins with premises about a particular person who is making a point, and

ends with a conclusion to the effect that the person’s reasons are not good. some can be good arguments

example: fuel company arguing against global warming should be dismissed most of the time they are not good arguments

there might be something about the person we don’t like so we dismiss it 10.5 Deniers

Definition: begins with the premises about a particular person who is making a point, and end with the conclusion denying the conclusion of that person’s argument

good argument: admits to lying including now so he is not telling the truth (Arthur the liar) good if you know the reputation of the speaker bad if uses features that are irrelevant

10. 6 Fallacies of relevance (appeals to authority) is an argument that begins with premises about a particular person who is making a

claim, and ends with a conclusion endorsing that person’s claim. opposite of an ad hominem argument example: the person was well dressed so we should accept their conclusion 3 types of appeals to authority

Amplifier: we should place great weight on the persons’ point, they are very deserving of our attention

supporters: the person’s reason are especially compelling

amfiremer: affirmed that person’s point 10.7Amplifiers

Definition: begins with premises about a particular person who is making a point, and ends with a conclusion that we should place great weight on the person’s point.

can be good arguments: legitimate authority this is very rare

10.8 Supporters begins with premises about a particular person who is making a point and ends with

a conclusion and ends with the conclusion to the effect that the person’s reasons are especially compelling.

Example: good waren buffet & isaac mizrahi10.9 Affirmers

begins with premises about a particular person who is making a point, and ends with a conclusion affirming that person’s point.

if they said it is true differences from supporters is that the argument is true not that is argument has good

reasons even if you do not understand the argument if you accept it then it is an affirmer

10.10 popular opinion is an appeal that begins with premises about the popularity about a particular claim and

ends with a conclusion endorsing that claim. if enough people believe it then it must be true can be good depending on the sources and reliability of the population

10.11 Vacuity when an arguments starts by assuming what it’s supposed to establish circularity the argument is among the premises begging the question: you need to already have a good reason for believing the

argument self sealing: is irrefutable by any means example: you will then be doing exactly what you will be doing noe evidence can be brought against it it is not significant

10.12 Circularity and begging the question Circularity

fallacy that results when an arguments premises contain its conclusion are usually easy to notice

begging the question fallacy that results when you cannot have a reason to believe an arguments premises

unless you have an independent reason to believe its conclusion10.13 Self sealers

is a proposition or an argument that is irrefutable because it does not claim anything, it does not rule out any conceivable situation

Week 11 How to argue Refutations and varieties (11.1)Refutation

to refute an argument is to show that the argument is unsuccessful an argument may be unsuccessful because we are not entitled to accept its premises or

it may be unsuccessful because its premises do not support its conclusion Ways to refute

don’t support the conclusion

parallel reasoning point out the fallacies false premises counter examples reductio ad absurdum

Pitfalls Straw man

similar but not enoughFalse Dichotomy

things have to be either one way or another way.Parallel reasoning (11.2)

To refute an argument by parallel reasoning is to show that the arguments form is not valid or strong.

Find another argument that has the same form but is clearly a fallacy Example: If everyone had a bigger salary then everyone could afford a bigger house and

if everyone stands up at a ballgame then everyone will have a better view. The parallel argument must have exactly the same form and the parallel argument must

clearly be a fallacy Counter Examples (11.3)

a counterexample is an example that runs counter to a generalization: it thereby shows that the generalization is false

can be used to refute an argument that contains generalization in either the premises or the conclusion

Example: I should not change the baby’s diaper example: no one should eat the bread hard to find a counterexample when a guarding term is used

Reductio ad absurdum (11.4) reduce to absurdity is an argument that prove that a particular hypothesis is false, because it implies an

absurdity Example: the best way to fight theft is to get rid of the tangible media of exchange

False Dichotomy when the argument assumes that there are only two possible situations Example: you are either with us or against us switzerland. There is no neutrality Example: Socks and shoes all in the family

Attacking the Strawman (11.5) to misunderstand the argument or the hypothesis that you are trying to refute example: hussan argument

How to argue week 12 Lecture 12.1 Constructing your own arguments

how to pick votes quality of the arguments distribution how useful the arguments were new points

Lecture 12.2 Debate about smart phones Should smart phones be banned in schools

The apps are distracting the students don’t concentrate behaviors that are distracting should be banned so smart phones should be

banned Opposite: they should be allowed in class

Smart phones have apps that help you study anything that can help students learn should be allowed in school banning will lower students communication in an emergency so they should be allowed

Lecture 12.3 all conscious thoughts are finitely explainable (deductive) -review all conscious thought are finitely explainable due to the finiteness of words. could be false

Lecture 12.4 chocolate pudding will probably improve your mood. beware of arguments that you already believe in probably guarding term improves your mood improves is a causal claim

Lecture 12.5 Slippery slopes a series of small differences can be considered a significant difference fairness doesn't always require us to treat cases differently when they’re not significantly

different fairness fallacy

Lecture 12.6 to visit parents frequently shouldn’t be legalized (ambiguity) to make it legal will lessen the morality of the people the imperative to

Lecture 12.7 capital punishment (vacuity) circular logic you would have to accept the conclusion for the premise to be true

lecture 12.8 Refutation via parallel reasoning “if god does not exist neither do barbers” if god existed there would be no suffering in the world there are people with long hair in the world if barbers existed then there would be no

people with long hair in the worldLecture 12.9 Why Walter should shave his head