Phil 103: Part 2

Evaluation

We use different criteria for evaluating deductive and inductive arguments In deductive arguments, we determine whether the argument form is valid or invalid (whether or not the conclusion follows necessarily). In inductive arguments, we determine whether the argument is strong or weak(whether if the premises are true, the conclusion is likely to be true).

When are Logical Operators true?

When is a conjunction true? When both conjuncts are true. When is a disjunction true? When either or both disjuncts are true. When is an implication true? An implication is only false when the antecedent is true and the consequent is false.

Slippery Slope Fallacy

When we conclude that the conclusion of a chain of probabilistic reasoning is likely to follow from the beginning. Event A will probably lead to event B. Event B will probably lead to event C. Event C will probably lead to event D. Event D will probably lead to event E. Therefore, if Event A happens, event E is likely to happen. Two main reasons why slippery slopes are fallacious. 1. Probabilities decrease when multiplied. 2. These arguments usually "leave out" important steps. Probabilities decrease when multiplied. Event A will probably lead to event B.[P(B\A) = .80] Event B will probably lead to event C.[P(C\B) = .80] Event C will probably lead to event D.[P(D\C) = .80] Event D will probably lead to event E.[P(E\D) = .80] Therefore, if Event A happens, event E is likely to happen .0.80 X 0.80 = .64 X .80 = .512 X .80 = .4096

Content of the Argument

Whether an argument is adequate depends on what it is about (content). Mala was the best basketball player on her high school team. Therefore, we can expect that she will do well in college basketball. While this lends some support to the conclusion, whether it is adequate depends on information about Mala's high school team (maybe they all sucked), as well as her college team.

Formal Validity

Whether or not a deductive argument is valid, depends on its formal structure. A) P1 All A's are B's. P2 X is an A. C1 Therefore, X is a B B) P1 If P then Q. P2 P C1 Therefore, Q.

Three Kinds of Casual Fallacies

1. Post hoc ergo propter hoc (Post hoc for short): is committed when it is argued that something that occurs before some event must be its cause. Example: My child broke her leg after she was vaccinated, so vaccines cause broken legs. 2. Confusing cause and effect: is committed when an effect is identified as a cause and the cause is identified as the effect. Example: I have noticed that at night time when the streetlights come on, the sun goes down. So it must be the streetlights that cause the sunset. 3. Common cause: is committed when we claim that there is a causal relation between A and B when A and B are both caused by C. Example: One day Bill wakes up with a fever. A few hours later he finds red spots on his skin. He concludes that the fever must have caused the red spots and concludes that if he spends the day in a tub of cold water his spots will go away.

Four Forms of Valid Arguments

1.Affirming the Antecedent (Modus ponens) 2. Denying the consequent (Modus tollens) 3. Chain Argument (Hypothetical Syllogism) 4. Disjunctive Syllogism (There are many forms of valid arguments. We will learn about just four of them.)

Explaining the Weakness

A full explanation of a weakness involves two steps: 1.First, we need to explain the nature of the weakness we think we have identified. It is usually best to begin by explaining the relevant criteria for a sound argument. If a fallacy is diagnosed, it is best to name it only after the relevant criteria have been explained. The purpose of this part of the explanation is to ensure that the person understands what we are concerned about. We should always ensure that they understand the nature of a weakness before we try to persuade them that our diagnosis is correct. 2.The second stage of a full explanation is backing up our diagnosis. This involves reconstructing the argument, supplying missing premises, identifying the logical structure, and so on, in the way described in previous chapters. If done properly, our explanation should convince our interlocutor that their argument does indeed contain a weakness.

Loaded Terms

A loaded term is any term with 1)A precise and clear descriptive meaning, and 2)Either a positive or negative evaluative meaning. A loaded word is used to persuade one to accept the evaluation conveyed by the term. A loaded term must have both an evaluative meaning (positive or negative) and a descriptive meaning. It is used to persuade one to accept the evaluation conveyed by the term. An example of a loaded term: A car rental company called "Budget." It is the descriptive adequacy of the use of the term that makes it possible to insinuate the evaluative meaning. Some evaluative terms, such as good, evil, right, and wrong, lack a determinate descriptive meaning and therefore cannot function as loaded terms.

Vague Terms

A vague sentence has numerous possible meanings, and often some of these possible meanings will make the sentence true while others will make it false. We usually recognize that a vague sentence is true in at least one possible interpretation (i.e., that it is partly, or in some sense, true). If we are not careful, we can be led to think that it is also true on other interpretations, when in fact it is false. Example of a vague statements (in the form of an advertising slogan): Coke Is the Real Thing.

Examples of a Sound Argument

A) Valid and sound argument: P1 If something is a living thing then it needs nourishment in order to survive. P2 This caterpillar is a living thing. C This caterpillar needs nourishment in order to survive. B) Valid argument with false premises and a false conclusion. P1 All professors are mathematicians. P2 All mathematicians are good politicians C All professors are good politicians. C) Valid argument with false premises and true conclusion. P1 Cities in Europe are in Oregon P2 Eugene is a city in Europe C Eugene is in Oregon

Appeals to Anecdotal Evidene

An anecdote is a short story about a real person or event. My friend Mala went to Reggie's restaurant last summer. According to her, from the start of her experience she just knew the whole meal was going to be a disaster. The place had a horrible smell and she was greeted by a host who was obviously drunk. But things get even worse...etc.It is tempting to rely on anecdotal evidence to draw strong conclusions. Therefore, don't go to Reggie's restaurant unless you want to have an awful time Anecdotes provide very weak and very limited support in arguments. Therefore, it would be prudent to look at some reviews online before deciding to eat at Reggie's restaurant.

Soundness

Any argument that is (1) logically strong, and (2) has true premises/conclusion(s) is a sound argument. A deductive argument that is (1) valid and (2) has true premises/conclusion(s) is also a sound argument.

Validity

How do we determine the validity of a deductive argument? Well, every deductive argument contains at least one truth functional statement. Truth functional statements contain at least one logical operator. Logical operators combine simple statements into complex statements.

Deductive Reasoning

Deductive arguments: if the premises are true, then the conclusion is necessarily true. (Highest "degree" of logical strength). Inductive arguments: even if the premises are true, and the argument has logical strength, the conclusion could still be false.

Appeals to Ignorance

Defending a claim by appealing to the fact that there is no evidence that it is false. Of course I believe that big foot is real. After all, no one has been able to prove that he doesn't exist.How could the absence of evidence that a claim is false (by itself) ever support that it is true? I can't prove that my lover isn't cheating on me, so they must be cheating on me. There is no way to prove that God doesn't exist. Therefore, God must exist. If the absence of evidence against something (by itself) counted as a reason for believing it, what would that mean? We would be required to believe a lot of absurd things. A pack of hyper-intelligent dolphins have been going around manipulating the price of gold. The world is going to end at exactly 4:21 pm this Friday. I guess there's no point in doing my weekly assignment for PHIL 103! Sometimes the absence of contrary evidence for a claim can lend support to the claim that it is true. But only when we already have good reasons to think that claim is true. Suppose you are trying to figure out what's wrong with your car, and you suspect that a worn-out spark plug is causing a popping sound (but you're not sure). If you were to find out that the air-filter was clean and working properly, this would lend some support to the conclusion that the spark plug is causing the problem. Here the absence of contrary evidence (i.e., having no reason to think that the problem is the air-filter) adds some justification for the claim that the problem is the spark plug.

Disjunction

Disjunction: The statement p or q is a disjunction. It is true when p is true, or when q is true, or when p and q are both true; it is false when both p and q are false. For example: Either Mac did it or Bud did it. This statement is true if either or both of its component statements, or disjuncts, is true. If both disjuncts are false, then the disjunction as a whole is false.

Disjunctive Syllogism

Either p or q. Not-p. Therefore, q. Either I drive a Civic, or I drive a Jetta. I don't drive a Jetta. Therefore, I drive a Civic.

Adequacy

Even if our argument has true premises that are relevant to the conclusion, those premises may not be adequate to support the conclusion. We often warn against "jumping to conclusions." Before we can assess an argument's adequacy, we need to ask what degree of strength it claims to have. 1. The ground is wet. It probably rained last night. 2. The ground is wet. Therefore, it must have rained last night. The first argument is adequate, the second isn't (at least if taken literally). •Jackie has a part time job and goes to the UO. Therefore, all students at the UO have part time jobs. •Of the 10 UO students I asked, half had part time jobs. Therefore, roughly half of UO students have part time jobs. •In a random sample of 1000 UO students, 36% were found to have part time jobs. We can conclude that approximately 36% of all the students at the UO have part time jobs. •Upon registration the UO asked every student whether they have a part time job. 40.7% said that they did. Therefore, 40.7% of UO students have part time jobs. Adequacy can come in degrees: No support Strict Proof

Chain Argument

If p then q. If q then r. Therefore, if p then r. If I drive a Civic, then I drive a Honda. If I drive a Honda, then everyone admires me. I drive a Civic. Therefore, everyone admires me.

Denying the Antecedent

If p then q. Not-p. Therefore, not-q. If I drive a Civic, then I drive a Honda. I do not drive a Civic. Therefore, I do not drive a Honda.

Denying the Consequent

If p then q. Not-q. Therefore, not-p. If I drive a Civic, then I drive a Honda. I do not drive a Honda. Therefore, I do not drive a Civic.

Affirming the Antecedent

If p then q. p. Therefore, q. If I drive a Civic, then I drive a Honda. I drive a Civic. Therefore, I drive a Honda

Affirming the Consequent

If p then q. q. Therefore, p. If I drive a Civic, then I drive a Honda. I drive a Honda. Therefore, I drive a Civic.

Implication

Implication: The statement if p then q is an implication. The two component sentences in an implication have different names since, unlike conjuncts and disjuncts, each plays a different role: the first is called the antecedent, and the second is called the consequent. An implication such as if p then q is false only when p is true and q is false; in all other cases (i.e., when p is false, or when q is true), it is true. For example: If Mo studies hard, then they will get an A average. This statement is true if both the antecedent and the consequent are true, that is, if Moe studies hard and also gets an A average. And it is clearly false if the antecedent is true while the consequent is false: if Moe studies hard and does not get an A average.

Appeals to Authority

In many cases, appeals to authority are irrelevant. But when they are relevant, we still need to question their adequacy: 1. Authority must be identified. 2. The authority must be generally recognized by experts in the field. 3. We can only appeal to an authority regarding claims within their field of expertise. 4. The field must be one in which there is genuine knowledge. 5. There should be consensus among experts about the claim.

Induction by Confirmation

Induction can be used to provide support for a hypothesis.A hypothesis is a principle or statement that, if true, would explain the event(s) or situation(s) to which it applies: for example, that excessive exposure to sunlight causes skin cancer. Induction by Confirmation •The form of induction by confirmation arguments is:If h then o.It is probable, therefore, that h. •In this schema, h stands for a hypothesis and o stands for an observation statement that is logically deducible from h. •Induction by confirmation is widely used in the sciences, especially in the physical and natural sciences (thought it appears in other contexts as well). For example: If the theory of general relativity is true, then it follows that light rays passing near the sun will be bent. During the solar eclipse of 1919 it was observed that light rays passing near the sun were deflected. It is probable, therefore, that the general theory of relativity is true. To test the truth of a hypothesis we follow a two-stage procedure:First, we deduce from the hypothesis a number of observation statements. An observation statement is an empirical prediction, which states that under certain conditions a certain fact will be observed. •By deducing observation statements from our hypothesis, we are claiming that, if our hypothesis is true, then we would expect to find that these empirical predictions are true.Second, we make observations to determine whether or not our empirical predictions turn out to be true. If our actual observations agree with the predicted observations, they provide confirming Instances for the hypothesis.

Inductive Reasoning

Inductive arguments are distinguished from deductive arguments by the fact that they do not guarantee their conclusions. The ability of valid deductive arguments to guarantee their conclusions derives from the fact that deductive reasoning merely makes explicit information that is already contained in the premises. This characteristic reveals the major weakness in deductive reasoning: its usefulness is limited to exploring the implications of what we already know or assume to be true. Genuinely new knowledge cannot be derived from deductive reasoning alone. For that, we must rely upon inductive reasoning. •Our current knowledge is indeed necessary as a basis for such discoveries, but it is not sufficient. Genuinely new knowledge can arise only through the use of inductive forms of reasoning. •Inductive reasoning is thus more powerful than deductive reasoning.•But the power of inductive reasoning comes at a price: the conclusion of an inductive argument can never be more than probably true. •The probability that a conclusion reached through inductive reasoning is true may be very high and may even approach certainty. But certainty can never, in principle, be achieved. •There is only one way of achieving certainty through reasoning, and that is by using a deductive argument. If we want to reach new knowledge that goes beyond what is implicit in our premises, we have to settle for something less than certainty

Casual Fallacies

It turns out to be really hard to say what exactly a cause is, and it's often misleading to say that a single event has a single cause. Lightning caused the forest fire. Or was it the presence of oxygen? Or was it the fact that it hadn't rained in several months. Or was it one of the innumerable factors that led up to these conditions being met. We usually want to find one condition that, along with the other necessary conditions, is sufficient to bring about the effect. For the sake of simplicity, the examples of causal fallacies we look at will assume that we are talking about this one condition.

Simple and Complex Sentences

Let's start with this distinction. Recall: a statement is a sentence that can be true or false. Simple Statements: do not contain other statements. Also called "atomic" statements. 1. It is raining. 2. Dolphins are mammals. Complex Statements: contain more than one statement. 1. It is raining and I am getting wet. 2. Either dolphins are mammals or they are some other kind of creature. Note that these are combinations of two separate statements.[it is raining] and [I am getting wet]

Logical Operators

Logical operator are words (or symbols) that are used to combine simple statements into complex statements. 1. You can have cake OR you can have ice cream. 2. If you are a student, THEN you can apply for scholarships. 3. IT IS FALSE THAT it is currently snowing in Eugene. We will look at four different logical operators: 1. Negation NOT 2. Conjunction AND 3. Disjunction OR 4. Implication IF... THEN... (also called a conditional)

Deductive Arguments: Validity

Only deductive arguments can be valid (or invalid). Inductive arguments cannot be valid because their conclusion is never guaranteed. An argument is valid when the conclusion follows necessarily from the premises. If the premises happen to be true, there is no way the conclusion could be false. (This means: the premises entail the conclusion.) If the conclusion does not follow necessarily from the premises, the argument cannot be valid.

Examples of Deductive Arguments

P1 Either the Ducks won, or they lost. P2 They didn't lose. P3 Therefore, the ducks won! P1 All birds can fly. P2 Penguins are birds. C1 Thus, penguins can fly.

Examples of Inductive Arguments

P1 The forecast is calling for rain tomorrow. P2 The forecast is extremely accurate. C1 Therefore, we can expect it to rain tomorrow. P1 Every single rose we've ever examined has had its thorns. C1 The roses in Django's garden will likely have thorns.

Truth Functionality

Recall that all statements can be either true or false. That is, they have a truth value. For simple statements, this is relatively straightforward (provided we have adequate knowledge). 1. Eugene is located in Oregon. 2. No humans can teleport. The truth value (i.e., truth or falsity) of a complex statement depends on two things: 1. The truth values of the simple statements of which it is made up. 2. The type of logical operator used to combine the simple sentences. The term logical operator is sometimes called a sentential connective.

Deductive Arguments

Recall that when we assess any argument, we are interested in two different things: 1. Whether it is logically strong. For deductive arguments, we ask whether they are valid or invalid. 2.Whether its premises are true.

Consequence of the Argument

Sometimes it is okay to accept weak arguments if the cost of doing so is insignificant, but the potential risk of not accepting it is high. I decided not to go swimming in the lake today because some kids told me that a bunch of toxic waste had been spilled in it. I think they were probably messing with me, but you never know.

Slippery Slope Fallacy (Part 2)

Sometimes we encounter slippery slope arguments that omit the chain of premises: I failed my biochemistry midterm. Looks like I'm going to be washing dishes for the rest of my career. The following argument does not commit this fallacy. If you go to university then you are likely to develop critical thinking skills. If you go to university, you are also likely to become more independent and responsible. If you go to university you are more likely to develop a personal and professional network. Therefore, you should go to university.

Appeals to Authority (2. The authority must be generally recognized by experts in the field.)

The authority must be generally recognized by people in their field. My uncle Tom has been reading a lot about Roman history, and he says that Caesar didn't cross the Rubicon until 48 BC. (Wrong) In his renowned study Bread and Circuses Paul Veyne suggests that the Romans practiced eugetism: a complex form of gift giving that functioned to redistribute wealth and provide services for the poor.

Appeals to Authority (4. The field must be one in which there is genuine knowledge.)

The field of knowledge must be one in which there is genuine knowledge. Rudy is really into alchemy. He claims that it is possible to create miniature fully-formed humans called homunculi. (Wrong) Historians of the 16th century, such as Franz Hartmann have shown that the alchemist Paracelsus believed that it was possible to create miniature fully-formed humans called homunculi.

Appeals to Authority (3. We can only appeal to an authority regarding claims within their field of expertise.)

The particular matter in support of which an authority is cited must lie within his or her field of expertise. My sociology professor is really smart. She told us that science is all just a social construct, so I guess I shouldn't bother taking biochem. (Wrong) My sociology teacher is really smart. She uses actor-network theory to study how scientific knowledge is produced. Based on her research, she doesn't think that there is such a thing as "value free" science.

Conjunction

The statement p and q is a conjunction. It is true only when p is true and q is true; it is false when p is false, or when q is false, or when both p and q are false. For example: Ted and Alice have been married for six years, and they have no children. This statement is true only if both its component statements, or conjuncts, are true. If either conjunct is false, then the conjunction as a whole is false.

Negation

The statement p is false is a negation. (Sometimes, negations are written as not-p.) A negation is true when its component statement is false, and false when its component statement is true. Thus, the statement p is false is true when p is false, and false when p is true. For example: It is false that falcons mate while flying. This statement is true if the statement falcons mate while flying is false. If falcons do mate while flying, then the statement is false.

Appeals to Authority (5. There should be consensus among experts about the claim.)

There should be consensus among the experts in the field regarding the particular matter in support of which the authority is cited. The economist Joseph Stiglitz argues that an optimal supply of local public goods can be funded entirely through capture of the land rents generated by those goods. Therefore, if we impose a land-value tax, we will be able to finance public healthcare. (Wrong) Nobody in the field of chemistry regards alchemy as a science. Therefore, we can dismiss the central tenets of alchemy as irrelevant to the study of chemistry.

Two Forms of Invalid Arguments

•The fallacy of denying the antecedent •The fallacy of affirming the consequent

Counter-Arguments

•A counter-argument attempts to show that someone's conclusion is false or problematic by constructing a different argument altogether to support a conclusion that is inconsistent with the original conclusion. •Every counter-example ignores the premises of the original argument and presents an independent set of reasons in support of a contrary conclusion. •Every weak argument is therefore open to a counter-argument. In fact, counter-arguments can often be developed against arguments whose weakness we are unable to identify. •If the argument is weak, we ought to be able to describe the weakness in such a way as to persuade our interlocutor. But if, as sometimes happens, we cannot do so, we might have to concede that our refusal to accept it may be irrational. •In these circumstances it can be very useful to attempt to develop a counter-argument. If we can develop a plausible one, then we have a good reason to believe that the argument is weak and that we are not being irrational. •Moreover, a good counter-argument can often suggest what is weak about the original argument .•To develop good counter-arguments we must be familiar with the subject matter under discussion and care about the issue as well. Counter-arguments cannot be developed merely as a reaction against an argument that looks weak.

Absurd Examples

•A more effective way of displaying a fallacy is the method of absurd examples. This method is similar tothe method of counter-examples but can be used against a broader range of weaknesses and are often pretty damn effective. •It involves constructing an argument that is parallel to the weak argument, but which has true or plausible premises and an obviously false or absurd conclusion.For example: Remy: As far as I'm concerned, people who are against teaching scientific creationism in the schools are communists. They are all atheists, after all, and all communists are atheists. Mariana: Don't be silly, Remy. That's like arguing that since all men have two eyes and all cats have two eyes, all men are really cats. Mariana's reply shows the weakness in Remy's argument by challenging its structure. Both arguments have an identical structure:All As are Bs.All Cs are Bs. Therefore, all As are Cs. •To be effective, an absurd example must be closely similar to the original argument. •The similarity always involves an identical structure, but it often involves similarity of content as well. •In general, the more closely an absurd example resembles the original argument, the more effective it will be in showing a weakness. •The previous example relies on an absurd example with the same logical structure as the fallacious argument. •Here is an example that relies mainly upon similarity of content: Walter: I think the government should ban all pornographic publications. It really bothers me to think of all those people reading all that mindless stuff.Will: Great argument, Walt. And I think the government should ban the Baltimore Sun. It really bothers me to think of all those people reading all that mindless stuff. •Will's absurd example is structurally identical to Walter's argument, but its success as an absurd example depends not so much on this similarity as on the •To be effective the absurd example should also use premises that are obviously true and uncontroversial, so that someone cannot reject it on the ground that it relies on unacceptable premises. •Sometimes, we can get away with hypothetical premises.Will, for example, may not be bothered at all by the thought of people reading the Sun, but pretends to be in order to make his point. •The main drawback to the absurd example method is that it is often difficult to invent a good absurd example on the spur of the moment. •If we use a bad absurd example, we give our interlocutors a plausible excuse to ignore the serious point we are trying to make on the ground that we have missed the point of their argument. •The greatest strength of the absurd example method, on the other hand, is that it places this person on the horns of a very sharply defined dilemma: either they must accept our absurd conclusion, or they must admit that their argument fails to support their conclusion.

Loaded Questions

•A real question attempts to elicit from a respondent information or opinions and, presumably, the questioner leaves it up to the respondent to answer it. •Loaded questions, by contrast, are not genuinely interrogative. Either they strongly imply the presuppositions that make them intelligible or they are really disguised claims. For example: On a scale of one to ten, how ugly would you say the University of Oregon's Duck logo is? Complex questions contain an assumption that any possible answer will confirm. Complex questions thus are a way of making a claim without appearing to do so. Rhetorical questions might seem like they are asking for new information from a respondent, but they are really disguised statements. Framing questions are posed in order to raise a possibility in the absence of evidence

Appeals to Authority (1. Authority must be identified.)

•Authority must be identified. Scientists have shown that... (Wrong) In their recent study, Campbell et al. have shown that...

Inductive Generalization

•The inductive generalizations we will look at have the following form: Z percent of observed Fs are G. It is probable, therefore, that Z percent of all Fs are G. For example, suppose we want to know what percentage of students at a particular university believe in god(s). Since, it is extremely difficult to ask every student at the university whether they believe in god(s), the more routine procedure is to select a sample of students and determine their religious beliefs and then to generalize the results to the whole student body. Inductive Generalization •Sampling involves observing a portion of a population in order to draw a conclusion about the entire population. •Whenever we use a sample of some population as the evidence from which we draw a conclusion about the whole population, our reasoning will be in the form of an inductive generalization. Thus, our example would be written out as follows: Sixty percent of students at the University of X who were questioned believe in god(s). It is probable, therefore, that approximately 60 percent of all students at the University of X believe in gods.

Weaknesses of Induction by Confirmation

•FIRST: Is the number of confirming instances relatively high? •One confirming instance of a hypothesis usually does very little to show that the hypothesis is true. It is therefore important to gather a large number of confirming instances before asserting that the hypothesis is probably true. •How large this number should be depends upon several factors: the range of different kinds of confirming instances, the scope of the hypothesis (i.e., does it apply to a large or small range of phenomena?), and whether the hypothesis is consistent with other well-established hypotheses.•In general, the larger the number of confirming instances, the stronger the argument and the more likely it is that the hypothesis is true. •This means that if the number of confirming instances for some hypothesis is relatively small, the argument could be charged with violating the criterion of adequacy. SECOND: Are there any disconfirming instances? •A disconfirming instance arises when an observation statement that is predicted by the hypothesis is found to be false. •Unlike the first weakness, which is a matter of degree, the presence of any disconfirming instances does not merely weaken the hypothesis, it refutes it altogether.

Counter-Examples

•Fully explaining a weakness sometimes can be very difficult. •The method of counter-examples is a short-cut method that is easy to use and can sometimes be remarkably effective. •However, its use is limited to arguments that rely upon a generalization in the premises that can be challenged as being unacceptable. •The method consists simply of presenting an exception to the generalization that shows that it should not be relied upon in the way the original argument does. •For example: Mike: You should try the wine cooler I just bought. It's really good. It is a new product, just put on the market by the producers, so it's bound to be better than their old ones.Elaine: Just like the new Coke, eh?Elaine attacks the missing premise of Mike's argument, that a new product is always better than existing products, by citing an example of a new product that was (or was commonly believed to be) inferior to the product it replaced. In this respect, counter-examples are logically adequate. in the face of a generalization, a single counter-example is all that we need to identify a flaw.

Humor

•Humor should not be used as a substitute for rational argument. In argumentative contexts, any use of humor functions independently of reasons in favor of the argument's conclusion .•When we use humor to divert attention from a weakness in our argument or to have some fun at the expense of our opponents, no reasons have been provided to believe that our position is stronger than that of our opponent. If our argument was weak before we added some humor, it will be just as weak after.

Irrational Techniques of Persuasion

•Irrational techniques of persuasion are usually considered fallacies because they pretend to supply (but don't really) reasons for one to accept an argument. •Unlike the other fallacies we've looked at so far, these ones do not follow the structure of an argument (with clear premises and conclusions). It is usually better to treat them not as arguments at all but merely as irrational techniques of persuasion •Loaded Terms •VagueTerms •Loaded Questions •Complex Questions •RhetoricalQuestions •Framing Questions •False Confidence •Selectivity Irrational Techniques of Persuasion •Misleading Statistics •Humor •RedHerring •Guilt by Association •Persuasive Redefinition

Selectivity

•Many judgments rest upon a complex body of evidence. Inductive generalizations, for example, rest upon a number of particular instances, and their strength depends upon these instances being a representative sample of the entire population. •Since populations are not usually homogeneous, we can be misled by an unrepresentative sample. This fact makes it possible for someone to create a misleading impression by bringing unrepresentative examples to our attention.

Misleading Statistics

•One type of selectivity involves the selective use of statistics. •For example, although it is often useful to know the average value of something, averages can be quite misleading. Suppose we are told that each player on a specific basketball team scores an average of 18 points a game. This is a lot of points per game! It is unlikely that every player actually scores this much, especially given that some positions require functions other than scoring e.g. setting screens, making assists, etc. What is more likely is that a few players score a lot of points and—in calculating the average—it appears like everyone scores a considerable number of points. Based on this average, it would be misleading to say that every player on the team is a high scorer, as this is not necessarily the case.

Guilt by Association

•One way of attacking an opponent or an opponent's position is by suggesting a similarity with another person or position that the audience regards in an unfavorable light. •Guilt by association involves a faulty analogy. Example: You have built up quite an expensive collection of wine in the last three months. I guess you will soon be sending your children to private schools, like other bougie people in the area.

Persuasive Redefinition

•Persuasive redefinition is the redefinition of a familiar term or phrase that has both a descriptive and an evaluative meaning in such a way as to change its descriptive meaning while keeping its evaluative meaning the same. •Consider the term poet. The dictionary gives us one definition of a poet a writer of verse. This is the descriptive meaning of the term. But the word can also be used with a strong positive evaluative meaning: to describe someone as a poet is normally to praise him or her. If we wanted to capitalize on this evaluative meaning, we might try a persuasive redefinition that involves dropping the requirement that a poet actually has to write verse: a poet is a person with a deep and vivid imagination

Statistical Syllogism

•Statistical syllogisms we will look at have the following form: Z percent of all Fs are g.x is an F. There is a Z percent probability, therefore, that x is g. •Statistical syllogisms always start from a generalization and use it as the basis for determining the likelihood that it will apply to a particular individual case. •So while in inductive generalizations, we move from the particular to the general, in statistical syllogisms, we move from the general to the particular. •For example, if we want to predict how likely it is that a particular student at the University of X believes in god(s), we would start with the conclusion of our previous inductive generalization and develop the following statistical syllogism: Sixty percent of students at the University of X believe in god(s). Brittis a student at the University of X. There is a sixty percent probability, therefore, that Britt believes in god(s).

Inductive Reasoning Pt. 2

•The strength of inductive arguments depends not on their form but on their content .•This means that we cannot produce a catalogue of logically strong inductive argument forms as we could for valid deductive arguments. •There are certain important inductive argument forms, but these forms by themselves tell us nothing about the logical strength of the arguments. To determine the strength of an inductive argument, we must always examine its content. For example, as we saw in section 8.2, in order to determine whether appeals to authority are legitimate, we have to examine the particular authority being appealed to and the particular claim involved. There are four types of inductive arguments that are widely used and that are strong arguments when certain conditions are met. Each inductive argument form is prone to its own type of weaknesses, so it is important to be able to recognize the form of an inductive argument before assessing it. 1. INDUCTTIVE GENERALIZATION 2. STATISTICAL SYLLOGISM 3. INDUCTION BY CONFIRMATION 4. ANALOGICAL REASONING

False Confidence

•This technique is used by those who believe that what they are saying is true, but who want their audience to accept the claim without critical scrutiny. It is a way of suggesting, rather than saying, to the audience that there is no need to ask for the evidence. •If the claim is one we think could be true, and especially if we think the speaker just might know something we don't, we can be taken in by the speaker's confidence. •As you might imagine, this relationship between the human psyche and human speech can and does have troubling social implications. •What are some social groups that tend to get taken more seriously (or their statements treated as fact) simply because of their confidence? How might other people—given their social location—be taken less seriously?

Strong and Weak Analogies

•To determine the strength of an analogy, we examine the similarities and dissimilarities between the two cases .•A strong analogy is one in which there is a large number of relevant similarities and a small number of relevant dissimilarities between the cases. A weak analogy is the opposite. It is important that the similarities and dissimilarities are relevant. For example: The fact that both riding a bicycle and driving a car are done in a sitting position is not a relevant similarity. The fact that I learned to ride a bicycle in June whereas I am proposing to teach myself to drive a car in September is not a relevant dissimilarity. On the other hand, the fact that both require good physical coordination is a relevant similarity. And the fact that cars are faster and more powerful than bicycles is a relevant dissimilarity. •The relevance of a similarity or dissimilarity depends upon the target feature of the analogy and the conclusion being inferred. •Determining the strength of an analogy involves weighing the relevant similarities against the relevant dissimilarities.

Weaknesses of Statistical Syllogism

•To determine whether a statistical syllogism is weak, it is necessary to look beyond the premises for any other information that might be relevant. The question we need to ask is:○Is there additional relevant information available concerning x that has not been included in the premises? •For example, if we know that Britt is a regular churchgoer, then it is likely that the chance that he believes in god is much higher than 60 percent. Or if we know that Britt refuses to go to church even for family funerals or his friends' weddings, then it is likely that the chance that he believes in god is much less than 60 percent. Or if we know that Britt is a history major and that only 40 percent of history majors believe in god, then it is likely that the conclusion of our argument will be false. •Whenever we use or assess a statistical syllogism, it is important to ensure that no relevant information has been overlooked. When a statistical syllogism leaves out relevant information, we can usually charge it with violating the criterion of adequacy, since the missing information significantly weakens the argument.•In some cases, however, leaving out relevant information will lead to the charge of violating the criterion of relevance.For example, if it is known that Britt has explicitly stated that he is a committed atheist, the appeal to the generalization about University of X students becomes quite irrelevant.

Weaknesses of Inductive Generalization

•Two possible weaknesses in inductive generalizations, both of which pertain to the nature of the sample. •The first and most important is that the sample may not be representative of the population it is drawn from. If it is an unrepresentative or biased sample, the argument is significantly weakened. •So when assessing any inductive generalization we should always ask: Is the sample representative? In other words, is the sample of observed Fs referred to in the premise representative of the entire class of Fs referred to in the conclusion? •Ideally, the sample should reflect the same percentage distribution as the entire student body at the University of X in regard to degree program, major, year, grade average, age, sex, place of birth, type of religious upbringing, drinking habits, etc. •The more closely the sample is representative of the entire student body, the stronger the argument. Weaknesses of Inductive Generalization •The second weakness that can arise with inductive generalizations is that the sample may be too small, and thus there is a second question we should ask: Is the sample large enough? •Even if a sample is adequately representative, it may nevertheless be so small that an inductive generalization from it is weak. In general, the larger the sample the stronger the argument .•However, as the size of the sample is increased, the increase in strength becomes smaller with each additional increase in the size of the sample. For example, an increase from 20 to 40 produces a much greater increase in strength than an increase from 220 to 240 .•In practice, therefore, we can often work with relatively small samples, especially if the population is homogeneous and we are careful to ensure that our sample is representative. •Even when the premises of an inductive generalization are acceptable and relevant, if the sample is unrepresentative or too small, then the premises will be inadequate to support the conclusion. •The second weakness that can arise with inductive generalizations is that the sample may be too small, and thus there is a second question we should ask: Is the sample large enough? •Even if a sample is adequately representative, it may nevertheless be so small that an inductive generalization from it is weak. In general, the larger the sample the stronger the argument. •However, as the size of the sample is increased, the increase in strength becomes smaller with each additional increase in the size of the sample. For example, an increase from 20 to 40 produces a much greater increase in strength than an increase from 220 to 240. •In practice, therefore, we can often work with relatively small samples, especially if the population is homogeneous and we are careful to ensure that our sample is representative. •Even when the premises of an inductive generalization are acceptable and relevant, if the sample is unrepresentative or too small, then the premises will be inadequate to support the conclusion.

Red Herring

•When responding to a criticism of some position we hold, it is often tempting to ignore the criticism and launch a counter-attack on our opponent by raising a different issue altogether. When we do this we have introduced a red herring. •When using the red herring technique we are attempting to avoid a criticism by shifting the discussion to a new topic on which we can attack the critic.

Analogical Reasoning

•Whenever we encounter something we do not understand, it is a natural reaction to try to understand it by reference to something that is familiar to us .•In such cases the reasoning presupposes an analogy between two things (objects, classes of objects, situations, relationships), one of which is familiar and one unfamiliar. •The quality of an analogy depends upon the purpose of drawing it. If the purpose is merely to clarify a difficult concept, any analogy will be a good one if it succeeds in clarifying the concept. •In general, any analogy that helps us to understand something can be a good one •Our concern is with analogies that are used in arguments, that is, where the analogy is being used to provide support for a conclusion. Here we need to be careful in choosing our analogies, for a weak analogy will fail to provide the support our conclusion needs. •Analogies by themselves are never sufficient to prove anything, and if an argument claims to prove its conclusion, any premise that introduces an analogy would be irrelevant. •A strong analogy can provide an adequate reason for conclusions that are claimed to be only probably true. For example: Last year I put some fertilizer on my strawberries in the fall and got about 20 percent more strawberries. You should do the same with your strawberries, since you've got the same kind of soil. You'll probably get more strawberries too. An analogical argument by properties has the form:x has A, B, C.y has A, B.It is probable, therefore, that y has C. In this schema, x refers to the analogue case, y refers to the subject case, and A, B, and C refer to properties. The target feature is C. As example: Canada Geese are water birds that nest in Canada in the early spring and migrate south to a warmer climate for the winter months. Ducks are also water birds that nest in Canada in the early spring. Therefore, ducks probably migrate south for the winter, too