Biostats Tips: Six Terms that Mean Something Different Statistically and Colloquially
By Kim Love and Karen Grace-Martin
Statistics terminology is confusing. Sometimes different terms are used to mean the same thing, often in different fields of application. Sometimes the same term is used to mean different things. And sometimes very similar terms are used to describe related but distinct statistical concepts. However, the terms that cause the most trouble are those with a different English colloquial and statistical meaning. This is particularly difficult because the definitions are often similar, if not exact.
Here are six of the most common terms:
You’re probably familiar with the difference between statistical significance, generally indicating a p-value that is below a threshold, and the colloquial meaning of large or important.
In everyday English, people use the terms Odds and Probability interchangeably. In statistics, they’re measuring the same general construct – how likely an event is to occur – on different scales. This difference in scales has a huge impact on how you interpret the value. Odds measure the probability (p) of an outcome relative to the probability that outcome doesn’t occur; i.e. p/(1-p).
In colloquial English, bias means prejudice. It’s bad. Bias isn’t always a good thing in statistics, but it doesn’t have that inherent value judgment.
In statistics it is a measure of the difference between the value of a population parameter and the theoretical mean value of a statistic that estimates that parameter. More often it comes from having an unrepresentative sample.
In statistics, a correlation is a specific measurement. It is a measure of the direction and strength of association between two variables.
On the other hand, the colloquial definition is much broader, to indicate any connection, match, or co-occurrence between individual events.
Colloquially, an error is a mistake.
Statistically speaking, an error is the difference between the measured value for one individual and the value predicted by a regression model. There’s no mistake involved here. Just variation.
Statistically, a phenomenon is random if individual outcomes are uncertain, but there is nonetheless a regular distribution of outcomes in a large number of repetitions.
While this is one usage of random in everyday English, it also often means strange or unexpected.
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