casual reasoning Flashcards
- What does correlation mean?
Connection between one or more things, measure of how things are related.
- What does causation mean?
Where a change in one variable affects the other variable; also referred to as cause and effect.
- What is accidental causation?
High correlation is the result of not having enough data. Correlation data are more useful when they involve a large range of causes.
- What happens when the causal direction is reversed?
Sometimes C is correlated with E not because C causes E, but because E causes C. Correlation by itself does not tell us which of these two stories (if any) is correct.
- What are hidden common causes?
Sometimes C and E are correlated not because one causes the other but because there is a hidden condition X that causes both C and E.
- Outline causation as a result of side effects
In some cases where C correlates with E because E occurs together with some other condition or side effect that actually causes E. The casual contribution from C to E might be non- existent or of lesser importance. The placebo effect is a good example of causation due to side effect. It refers to the real or felt improvement in a patient’s condition that is due to beliefs about the treatment rather than the medical efficacy of the treatment itself.
- What is the Pygmalion effect?
The Pygmalion effect originated from a study where teachers were told that some of their students were above average even through, they were randomly selected with the same average abilities. But the subjective expectation of the teachers somehow led to better performance by these students later on. The result has been replicated in other contexts, and this has important implications for education and management.
- Describe covariation and manipulability
If changes in one event correspond to changes in another event, then this makes it more probable that one causes the other. In reality, manipulating correlation can sometimes be difficult or even unethical to do.
- Outline casual relevance
Casual relevance: Suppose a student failed a course. She might have been lazy or having personal problems. Or perhaps she was ill on the day of the exam. All these factors could have contributed to her failure. They were ill casually relevant, each being a cause of her failure but none being the cause. The most important one is the primary or central cause.
- Outline casually necessary and sufficient conditions
Casually necessary and sufficient conditions: X is usually necessary for Y when Y would both happen without X, and X is casually sufficient for Y when X by itself is enough for Y. Water is casually necessary but not sufficient for our survival, and moving electric charges are sufficient but not necessary for the presence of a magnetic field. But X can be casually relevant to Y if X is neither casually necessary nor sufficient relevant to Y even if X is neither causally necessary nor sufficient for Y.
- Outline triggers
Triggers: A triggering cause is a cause that starts off a chain of events leading to an effect. Whereas a structural cause is a background condition that is casually relevant to the effect but which on its own is not sufficient for it.
- Outline proximity
Proximity: A proximate cause happen at a time near the occurrence of the effect, whereas a distal cause happened much earlier
- Outline randomness and casual determination
Randomness and casual determination: A random event is one that is not casually determined by what happen earlier. To say that an event is determined is to say that is must occur given what has happened earlier and the physical laws of our universe.
- Outline mill’s method of agreement
If two or more situations lading to an effect E has only one event C in common, then C is the cause of E.
- Outline mill’s method of difference
If one group of situations leads to an effect E, but another group does not, and the only difference between the two groups is that C is present in the former but not the latter, then C is the cause of E.
