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Simpson`s paradox
| Glossary of Statistical Terms |
What is true for the parts is not necessarily true for the whole. see also confounding.
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Парадокс симпсона, русский
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Paradox, английский
- N парадокс
- 1. a contradiction in conclusions indicating a fallacy in the assumption or logic. 2. a commercial expert system for the management of relational databases.
- From the greek ~ + dokein, to think more, 57 conventionally, an argument that apparently derives self-contradictory conclusions by valid deductions from acceptable premises (webster`s). more generally, any description or situation that is compelling enough to lead an observer into a vicious cycle involving mutually exclusive interpretations, indications or acts, force him to step out of or transcend the cycle and to construct a logically more powerful (->ordinality) cognitive system within which the vicious cycle has disappeared. e.g., "this sentence is false" is false when it is assumed to be true and true when it is assumed to be false. the resolution of this vicious cycle requires a logic that accepts self-reference which the propositional calculus does not. paradoxes appear not only in logic but also in interpersonal communication, e.g., double-bind, in social organization and might be the stimulus for morphogenesis.
Paradox(on), widerspruch, немецкий
Paradoxical breathing, английский
A condition affecting someone with broken ribs, where the chest appears to move in when he or she breathes in, and appears to move out when he or she breathes out
Paradoxical sleep, английский
Same as rem sleep
Paradoxology, английский
Книжн. речь, пересыпанная парадоксами
Paradoxum [i, n], латинский
Paradoxus, латинский
Paradoxus [a, um], латинский
Paradoxymoron, английский
A figure of speech that proposes a decision with two opposite choices that contradict each other. example the choice between coke and pepsi was an paradoxymoron.
Simpson, английский
Simpsonite, английский
Simpsono, английский
Simpson addict. example you are simpsono.
Simpson`s rule, английский
Confounding, английский
When the differences between the treatment and control groups other than the treatment produce differences in response that are not distinguishable from the effect of the treatment, those differences between the groups are said to be confounded with the effect of the treatment (if any). for example, prominent statisticians questioned whether differences between individuals that led some to smoke and others not to (rather than the act of smoking itself) were responsible for the observed difference in the frequencies with which smokers and non-smokers contract various illnesses. if that were the case, those factors would be confounded with the effect of smoking. confounding is quite likely to affect observational studies and experiments that are not randomized. confounding tends to be decreased by randomization. see also simpson`s paradox.
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Finite population correction, английский
When sampling without replacement, as in a simple random sample, the se of sample sums and sample means depends on the fraction of the population that is in the sample: the greater the fraction, the smaller the se. sampling with replacement is like sampling from an infinitely large population. the adjustment to the se for sampling without replacement is called the finite population correction. the se for sampling without replacement is smaller than the se for sampling with replacement by the finite population correction factor ((n −n)/(n − 1))½. note that for sample size n=1, there is no difference between sampling with and without replacement; the finite population correction is then unity. if the sample size is the entire population of n units, there is no variability in the result of sampling without replacement (every member of the population is in the sample exactly once), and the se should be zero. this is indeed what the finite population correction gives (the numerator vanishes).
Linear association, английский
Two variables are linearly associated if a change in one is associated with a proportional change in the other, with the same constant of proportionality throughout the range of measurement. the correlation coefficient measures the degree of linear association on a scale of −1 to 1.
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