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Causal argument – any argument that has a causal claim – “therefore, A causes B” – as its conclusion
- John Stuart Mill (1806–1873) is the figure who tried to spell out the rules of inductive, causal logic just as
- Aristotle (384–322 BC) had laid down some of the most important principles of deductive logic millennia earlier.
Mill’s five methods
- Method of agreement
- Method of difference
- Joint method of agreement and difference
- Method of concomitant variation – looking for an answer to the following question: “Why do we see more of a certain characteristic in one group than in another?” Mill’s insight is that the strength – that is, the frequency and/or severity – of an effect should vary in tandem with the strength of the cause.
- Method of residues (aka, process of elimination) – looking for an answer to the following question: “Which possible cause of a certain condition is the actual cause?” by testing one possibility at a time.
Controlled experiment – where investigators study two or more groups that are highly similar to one another except for their exposure to the suspected cause of some effect.
Example – in order to find out whether smoking causes lung problems, researchers follow two groups of people for many years. One group is made up of smokers and the other of non-smokers; otherwise, the groups are very much alike in terms of age, sex, ethnicity, occupation, etc. At the end of the experiment the researchers look to see whether or not lung problems are more common or more severe among the group exposed to the suspected cause, smoking.
A prospective study
Example – in order to find out whether smoking causes lung problems, researchers follow two groups of people for many years. One group is made up of smokers and the other of non-smokers; otherwise, the groups are very much alike in terms of age, sex, ethnicity, occupation, etc. At the end of the experiment the researchers look to see whether or not lung problems are more common or more severe among the group exposed to the suspected cause, smoking. studies describe a few minutes ago. Researchers believe they know the cause of their conditions. but they test their hypothesis to see if the effects show up
A prospective study
is another kind of controlled study, one that looks to the past. The experimental group is selected from a population that already exhibits the effect for which a cause is sought. It is then matched to a control group that lacks the effect but is highly similar in other relevant ways – age, sex, occupation, etc. Then a backward looking study of the histories of the two groups is done, looking for an antecedent condition or conditions present in the experimental group but absent in the control to justify a claim that the difference is the cause of the effect. In a retrospective study the effects are already present and recearchers are looking for the cause. In a prospective study the is already present and rearchers wait to see if the effect occurs
a study where one group, the control, receives a medically useless substance (a placebo) while the other group, the experimental group, receives the drug whose effectiveness is being tested. But neither those receiving the placebo/drug nor the experimenters know which group is which until after the study is completed.
- a cause is necessary if the effect cannot occur without it.
- Examples – oxygen is necessary for a fire to occur because if no oxygen, then no fire. Taking quizzes and tests is necessary for getting an “A” in this class; if you don’t take the quizzes and tests, then no “A.”
a cause is sufficient if, when it is present, the effect must occur.
Examples – getting all the answers right on all the tests and writing an excellent paper is sufficient for getting an “A” in this class; if the first thing happens, then the second will happen.
Individually necessary and jointly sufficient conditions (or causes) – a group of antecedent conditions where, if any of them individually is absent, the event will not occur but all of them collectively are present then the event does occur.
Example – “If a match is dry, and if the match head has the right chemical composition, and if there’s oxygen present, and if the match is struck hard enough against a surface that is rough enough, then the match will light.” The portion in red states the individually necessary and jointly sufficient conditions because if all those things happen then the match will light, but if even one of them individually doesn’t happen then the match won’t light.
Causal over-determination – when there are multiple sufficient causes for an event’s occurrence such that as long as even one of them remains, the event will occur.
- Examples –
- 1) An unlucky person develops three fatal diseases. Cures are discovered for two of them before he dies; nevertheless,
- 2) You apply for a job but arrive too late and, hence, aren’t even interviewed; later you learn that there was a ‘leading candidate’ for the job – the boss’s best friend’s sister – who was going to be hired no matter who else applied. Your not getting the job was causally over-determined.
Probabilistic cause – an antecedent condition whose presence makes the occurrence of the effect more likely than in its absence.
Example – driving recklessly does not mean that you will get into a serious auto accident, but it does make it more likely. Therefore, driving recklessly is a probabilistic cause of serious auto accidents.
Some fallacies related to causal reasoning
The post hoc fallacy – asserting that A caused B just because A came before B.
The fallacy of ignoring a common cause – failing to consider that although A and B always go together, A might not cause B and B might not cause A but that some third thing, C, causes them both
Confusing causes with effects – failing to consider that although A and B always go together, A might cause B; B causes A.
The fallacy of ignoring an intermediate variable – failing to consider that although A and C always or often go together, the causal sequence is more fully and accurately brought out by recognizing that there is a third factor, B, that intervenes between A and C.
All of these fallacies really represent warnings about the hazard of jumping to conclusions when engaged in causal reasoning!