Term
| Mills Methods are used to measure the strength of |
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Definition
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Term
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Definition
1) Method of Argument
2) Mehtod of Difference
3) Method of Concomitant Variation
4) Method of Residue |
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Term
| Mill's Method of Agreement |
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Definition
| A common factor. Multiple potential causal factors present. Phenomenon being analyzed only occurs when a common antecedent A is present. Then it is most likely the case that antecentent A is the cause. |
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Term
| Mills Method of Difference |
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Definition
| A common lacking. Multiple potential factors present. Phenomenon being analyzed does NOT occur when a common antecedent A is not present. It is most likely the cause that antecedent A is the cause. If we notice that ou tof all the potential causes the phenomenon NEVER occurs when a single potential causal factor is lacking, then that common potential cause that is lacking is probably the cause of the phenomenon. |
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Term
| Mills Method of Concomitant Variation |
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Definition
| A certian phenomenon P has a antecedent A. When A increases, P increases. When A decreases, P decreases. Then it is most likely the case that antecedent A cause variation in phenomenon P. Phenomenno varies in intensity when a single potential cause varies in intensity, then that potential cause is probably causally related to the phenomenon. |
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Term
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Definition
| A phenomenon has three parts and has multiple antecedents (A,B, and C). Antecenent A causes part of the phenomenon; B causes part of the phenomenon. It is likely that C causes the remaining part of the phenomenon. Knowing all of the other parts we can determine that the last causal factor is the cause of the unaccounted portion that remains. |
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Term
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Definition
| The person/thing/ect. that is the focus of the analogy. Usually found in the conclusion |
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Term
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Definition
| The person/thing/ect. that is used as teh basis for the comparison with the subject. Usually found in the premises. |
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Term
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Definition
| The features that are common to both the analogue and the subject. Common features mean to establish a connection between the subject and the analogue. |
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Term
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Definition
| A feature that is know to be present in the analogue. On the basis of a strong comparisson, this feature is inferred to be present in the subject. |
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Term
| 4 parts that make up arguments from analogy |
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Definition
subject
analogue
common features
inferred features |
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Term
Arguement for Analogy
Analysis |
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Definition
State the subject
State the analogue
State the common features
State the inferred features |
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Term
Arguments from Analogy
Critique |
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Definition
Is this a strong or weak argument from analogy?
Are the common features relevant to the inferred feature? Explain.
Are there any relevant dissimilarities? Explain. |
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Term
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Definition
Causal Analogy
Statistical Analogy
Moral Analogy
Aesthetic Analogy |
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Term
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Definition
| Common features are causally connected to the presence of the inferred feature. Relevance of similarities to inferred feature. |
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Term
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Definition
| Common features are statistically correlated with the presence of the inferred feature. |
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Term
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Definition
| Common features justifying a moral judgement about the analogue justify the same moral judgment about the subject. |
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Term
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Definition
| Common features justifying an aesthetic judgement about the analogue justify the same aesthetic judgement about the subject. |
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Term
Determine strength of arguments from analogys
Are common features relevant to the inferred feature? |
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Definition
| We need to make sure that the common features do support the presence of the inferred feature, or that the common features make it all the more likely that the inferred feature. (4 kinds of analogies) If the common features are relevant, then the conclusion made abou the subject is strengthened. |
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Term
Strenth of Arguement for Analogy
relevant dissimilarities? |
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Definition
| strength of an argument from analogy can be underminded if there is a relevant dissimilarity that weakens the connection between the common features and the inferred features. A relevant dissimilarity may show that despite the features that are common to the analogue and the subject, there is an important difference between the analogue and the subject. Given this difference, the connection between the analogue and the subject is weakended. |
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Term
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Definition
1) formal deductive reasoning- truth follow from truths.
2) non-formal inductive reasoning- a question of lielihood. |
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Term
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Definition
1)Fallacy of Relevance
2)Fallacy of Weak Induction
3)Fallacy of Presumption
4)Fallacy of Ambiguity |
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Term
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Definition
| One or more premises do not give direct support to the conclusion. One test would be removing the potentially irrelevant premise, and then to determine if the conclusion is weakended. |
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Term
| Fallacy of Weak Induction |
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Definition
| Premises contain some (good) evidence for the conclusion, but there is not enough evidence. The evidence presented in the premises is relevant to the conclusion,a dn so it cannot be a fallacy of relevance; there is simply not enought evidence to support the conclusion. |
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Term
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Definition
| The premises, in obvious or subtle ways, presumes the conclusion. In other words, the premises assume as true what they intend to prove as true. A presumption is made that dictates the outcome of the argument before the argument can even get off the ground. |
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Term
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Definition
| The premises contain words or phrases that result in misinterpretations, and conclusions derived from this misinterpretations are fallacious. Does the truth of the conclusion depend on how one reads/understands an ambiguous phrase in the argument? |
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Term
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Definition
| The offending element is the portion of the argument that is the source of the error in reasoning. The major component to informal fallacy questions is to give a good explanation, one that shows why the offending element is fallacious. You must reference one (or more) of the four types of fallacies, and give a clear and detailed explanation about why the offending element exhibits the type of fallacy indicated. |
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Term
| Steps for Informal Fallacies |
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Definition
A. State which of the four major kinds of fallacies is being exhibited in this argument.
B. State the offending element in the argument, the part of the argument exhibits the fallacy. Then, in a brief paragraph, explain why that protion of the argument exhibits that type of fallacy. |
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Term
Inductive Genteralizations
Analysis |
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Definition
State the population
State the sample
State the target characteristic |
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Term
Inductive Generalizations
Critique |
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Definition
Determine whether this is a strong or weak gemeralization based on your answers to the following questions:
*Is the sample size appropriate?
*Is the sample representative of the population (properly randomized, reflects diversity)?
*Is there an interviewer bias? |
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Term
Causal Assertions
Analysis |
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Definition
| State the specific causal assertions |
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Term
Causal Assertions
Critique |
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Definition
Is this a strong or weak assertion?
If strong, explain which method(s) suport this assertion how the method supports this specific assertion
If weak, which method(s) whould best give support to this assertion, and what extra information would be needed? |
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Term
Informal Fallacies
Analysis |
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Definition
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Term
Informal Fallacies
Explanation |
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Definition
State the offending element of the argument
Explain why the offending elements exhibits the chosen fallacy
If no fallacy is present, explain how the argument does not exhibit a fallacy. "this arguemtn probably is not a fallacy of weak induction because..." |
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Term
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Definition
| The overall set of people/things/ect. being analyzed. The population is usually found in the concluding statement of the generalization. Be sure to state the size of the population if given. |
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Term
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Definition
| the subset of the population that is under direct investigation. The sample is usually found in the premises-those people/things/ect. being surveyed or studied. Be sure the state the size of the sample and population if given. |
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Term
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Definition
| What is being studied in the sample and then generalized to the population. |
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Term
| 2 major criteria used when analyzing and inductive generalization |
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Definition
1) sample bias
*sample size
* representativeness of sample
2)interviewer bias |
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Term
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Definition
| when analyzing the strength of an inductive generalization, one must consider whether the size of the sample is adequate. A good sample is one where it reflects a large enough percentage of the population. There is no rule for sample size, but questions will generally have samples that are obviously adequate in size, or obviously too small. |
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Term
| Sample bias-Representativeness of sample |
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Definition
| a smaples is a good sample when it accuratley represents the population. The point of an inductive generalization is the study a sample, and then make some clain about he population as a whole based on the information learned from the sample. Ther generalization is reliable only when the sample really does represent the population. A samples that is biased, that misprepresents the population, will produce generalizations that are not reliable. |
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Term
| A small sample size may still produce a good inductive generalization if |
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Definition
| The target characteristic being anazlyed is invariant (where the characteristic doesn't vary very much at all from person to person) |
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Term
| A sample fails to be representative when |
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Definition
| not every member of the population has an equal chance to be a part of the smaple, and sort an elemtn of reandomness must be included in the construction of the sample. |
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Term
| When the population is not diverse, a sample is representative when |
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Definition
| it is a simple random sampling-each member of the population has a chance to be a part of the sample |
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Term
| When the population is diverse, a sample is representative when |
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Definition
| it reflects the diversity of the population. This can be done through stratified random sampling-the proportions of the dieverse population are carried over to the sample |
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Term
| Questions involving causal statments require |
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Definition
1)clear statement of the causal assertion
2) an analysis of the sccertion using Mill's Methods |
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Term
| Questions involving inductive generalizations require |
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Definition
A)state the population, the sample, and the target characteristic
B)Determine whether the inductive generalization is strong or weak, and explain your answer using sample bias, representativeness of sample, interviewer bias |
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Term
| Clear statment of causal statement |
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Definition
| you must clearly state the causal statement that is being asserted. The causal statement is either the affirmation (or denial) that a certian event/thing/ect. is the cause (or is not the cause) of a subsequent event/thing/ect. Typically, the causal statement is found in the conclusion of the question. |
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Term
| Analysis of the accertion using Mill's Methods |
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Definition
| you have to determine whether the causal assertion is good or bad, and you must use Mill's Methods in your analysis. Any answer given for this portion of the question must utilize Mill's Methods in some capacity. |
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Term
| A causal assertion may be a good one because |
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Definition
| it is suported by one or more of Mill's Methods; in this case you need to describe how the assertion is supported by the Method(s). |
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Term
| A causual assertion may be bad because |
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Definition
| it is not supported by any of the Mill's Methods; in this case, you need to descirbe why the assertion fails to conform to any of the Methods. |
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Term
| A causual assertion may be bad because |
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Definition
| it is not supported by any of the Mill's Methods; in this case, you need to descirbe why the assertion fails to conform to any of the Methods. |
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Term
| Questions involving arguements for analogy require |
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Definition
1)stating the four parts that makeup the argument (subject, analogue, common features, inferred features)
2)determine whether the argument from analogy is strong or weak and explain |
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Term
| If the common features are relevant |
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Definition
| then the presence of those common features in both the subject and the analogue increase the probability of the inferred feature being present in the subject |
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Term
| If the common features are irrelevant to the inferred feature |
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Definition
| then they do not provide strong support for the conclusion |
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Term
| Relevant dissimilarity may show that |
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Definition
| despite the featurse that are common to the analogue and the subject, there is an important difference between the analogue and the subject that weakens the argument. |
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Term
| Questions involving inductive generalizations require |
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Definition
1)state which of the 4 major kinds of fallacies is being exhibited in this argument
2)state the offending element in the argument, the part of the argument exhibits the fallacy. Then, in a brief paragraph, explain why that portion of the argument exhibits that type of fallacy |
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Term
| An argument is inductively strong when given it's premises |
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Definition
| it is deductively invalid and it is more probable than not that the conclusion follows |
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Term
| an argument is inductively weak when given it's premises |
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Definition
| it is deductively invalid and it is more probable than not that they conclusion does not follow. |
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Term
| Inductive generalizations are arguments concluding that |
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Definition
| something is the case about all or many things on the basis of what is observed about some of them. Presupposed in every inductive generalization is the ideas that what we observe in the sample is likey to be true of all members of the group. |
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Term
| Inductive generalizations consists of |
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Definition
1)premises descrbing a sample
2)as having a target charasteristic as reason for
3)a conclusion that all or some percentage of the pupulation has that target characteristic |
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Term
| The strength of an inductive generalization is a function of |
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Definition
| the representativeness of the sample. The more representative the sample, the stronger the arguements |
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Term
| A sample is representative of a population to the degree that |
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Definition
| the target characteristics found in the sample occur with the same frequency or in the same proportion as they occur in the population. |
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Term
| To access the representativeness of a sample we need to know |
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Definition
1)what different characteristics occur in the population
2)whether those charachteristics are relevant to the occurrence of the target characteristic. The more relevant diversity in the smaple, the more representative it is. |
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Term
| A random sample is selected by a method that gives each member is the populations |
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Definition
| an equal chance of being selected |
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Term
| A sample that is unrepresentative is called |
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Definition
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Term
| A causal statement is a statement that |
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Definition
| asserts or denies that one thing or type of thing cause another |
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Term
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Definition
| A statement asserting or denying that one thing or event or type of thing cause or is caused by another thing or type of things |
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Term
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Definition
| An argument in which at least one causual statement occurs either as a premise or as a conclusion |
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Term
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Definition
| An argument consisting of a causal generalizaion, and instance of caual circumstance, and concluding that a specific effect occurs. |
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Term
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Definition
| An argument consisting of a causal generalizaion, an instance of an effect, and concluding that an instance of a specific cause explains the occurence of the effect. |
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Term
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Definition
| An arguement consisting of a causal generalizaion and concluding with a prescription or recommendation for producing or preventing some effect |
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Term
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Definition
| An argument consisting of premises in suport of a causal statement |
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Term
| Mill's Methods provide four criteria for assessing the strength of arguments having a |
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Definition
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Term
| A causal conclusion is strong to the degree that it is supported by |
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Definition
| premises with evidence of one or more of mill's methods |
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Term
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Definition
| If circumstance F is the only circumstance always present whenever E occurs, then we have supporting evidence for the conclusion that F is the cause of E |
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Term
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Definition
| If E occurs whe F is present but not when F is absent, then we have supporting evidence for the conclusion that F causes E |
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Term
| Method of Concomitant Variation |
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Definition
IF one phenonmeon varies consistently with another, then we have supporting evidence that the two are causally related.
1)given 2 phenomena that vary consistenly, if one presedes the other, then we have supporting evidence that the former causes the later.
2)Given 2 phenomena that vary consistenly, if by altering one we can produce concomitant variation in the other, then we have supporting evidence that the former causes the latter. |
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Term
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Definition
| If one or ore parts of a phenomenon cause be causally esxplained by one or more parts of the antecedent circumstances, then we have supporting evidence that the reamining part of the phenomenon can be causally explain by the remaining antecedent circumstances. |
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Term
| An arguement for analogy draws a conclusion about |
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Definition
| one thing on the basis of an analogy to some other thing |
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Term
| 2 criteria of the inductive strength of an argument from analogy |
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Definition
| the common features are relevant to the inferred feature; and there are no relevant dissimilarities |
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Term
| A common feature is relevant to the presence of the inferred feature if it |
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Definition
| increases the likeihood of the presence of the inferred feature. |
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Term
| A common feature may be relvant to an inferred features in the following ways |
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Definition
1)causal analogy
2)stastical analogy
3)moral analogy
4)aesthetic analogy |
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Term
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Definition
| common featurs are causally connected to the presence of the inferred feature |
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Term
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Definition
| Common features are statistically correlated with the presence of the inferred feature |
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Term
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Definition
| common features justifiying a moral judgement about the analogue justify the same moral judgement aoub the subjects |
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Term
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Definition
| common features justifying an aesthetic judgement about the analogue justify the same aesthetic judgement about the subject |
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Term
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Definition
| a defect in an argument that consists in something other than false premises alone. |
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Term
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Definition
| one that may be identified by merely examining the form or structure of an arguement. Foudn only in deductive arguments that have identifiable forms. |
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Term
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Definition
| those that can be detected only by examining the content of the argument. Can affect both deductive and inductive arguments |
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Term
| Fallacies of relevance occur when |
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Definition
| premises of an arguemtn are not relevant to the conclusion. |
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Term
| Fallacies of weak induction occur when |
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Definition
| the premises, although possibly relevant to the conclusion, provide insufficent support for the conclusion. |
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Term
| Fallacies of presumption occur when |
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Definition
| the premises presume what they porport to prove. |
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Term
| Fallacies of ambiguity occur when |
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Definition
| the conclusion depends on some form of linguistic ambiguity |
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Term
| Fallacies of grammatical analogy occur when |
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Definition
| a defective argument appears good owing to a grammatical similarity to some arguemtn that is not fallacious. |
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Term
| 3 factors that underlie the commission of fallacies in real-life argumentation are in |
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Definition
1)the intent of the arguer
2)mental carelessness combined with unchecked emotions
3)unexamined presuppositions in the arguer's worldview |
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Term
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Definition
| The presence of this condition ALONE is capable of bringing about the effect |
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Term
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Definition
| The presence of this conditon must exist for the effect to occur at all. |
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Term
| Necessary but not sufficent |
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Definition
| the presence of a necessary condition does not ential that causal event will take place |
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Term
| Mill's Method of Concomitiant Variation: Simultaneous |
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Definition
| where antecedent and consequent reamins unclear |
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Term
| Mill's Method of concomitiant variation: Squential |
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Definition
| Where definite gap exisits between antededent and consequent |
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