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Show EPDEMIOLOGICAL AND STATISTICAL TERMS association A term signifying a relationship between two or more events or variables. Events are said to be associated when they occur more frequently together than one would expect by chance. Association does not necessarily imply a casual relationship. Statistical significance testing enables a researcher to determine the likelihood of observing the sample relationship by chance if in fact no association exists in the population that was sampled. The terms "association" and "relationship" are often used interchangeably. causality Relating causes to the effects they produce. Most of epidemiology concerns causality, and several types of causes can be distinguished. A cause is termed "necessary" when a particular variable must always precede an effect. This effect need not be the sole result of the one variable. A cause is termed "sufficient" when a particular variable inevitably initiates or produces an effect. Any given cause may be necessary, sufficient, neither, or both. confidence interval A range within which an estimate is deemed to be close to the actual value being measured. In statistical measurements, estimates cannot be said to be exact matches, but rather are defined in terms of their probability of matching the value of the thing being measured. etiology Cause. A term used by epidemiologists. P__________________________________ precision In statistics, the quality of being sharply defined or stated. One measure of precision is the number of distinguishable alternatives from which a measurement was selected, sometimes indicated by the number of significant digits in the measurement Precision can be contrasted with accuracy, which is the degree of conformity of a measure to a standard or true value. Often, however, this contrast is not relevant, because the true value is not known. probability (P value) The likelihood that an event will occur. When looking at differences between data samples, statistical techniques are used to determine if the differences are likely to reflect real differences in the whole group from which the sample is drawn or if they are simply the result of random variation in the samples. For example, a probability (or P value) of one percent indicates that the differences observed would have occurred by chance in one out of a hundred samples drawn from the same data. rate A measure of the intensity of the occurrence of an event. For example, the mortality rate equals the number who die in one year divided by the number at risk of dying. Rates are usually expressed 143 |