Seller posts within 1 day after receiving cleared payment - opens in a new window or tab. Keep things cool and comfortable with the stylish Denham Chelsea boot.
CREVO Geoff Leather & Wool Boot
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See each listing for international postage options and costs. Pagination for search results. It is calculated by applying a function statistical algorithm to the values of the items of the sample , which are known together as a set of data.
More formally, statistical theory defines a statistic as a function of a sample where the function itself is independent of the sample's distribution; that is, the function can be stated before realization of the data.
The term statistic is used both for the function and for the value of the function on a given sample. A statistic is distinct from a statistical parameter , which is not computable, because often the population is too large to examine and measure all its items. However, a statistic, when used to estimate a population parameter , is called an estimator. For instance, the sample mean is a statistic that estimates the population mean , which is a parameter. When a statistic a function is being used for a specific purpose, it may be referred to by a name indicating its purpose: However, a single statistic can be used for multiple purposes — for example the sample mean can be used to describe a data set, to estimate the population mean, or to test a hypothesis.
In calculating the arithmetic mean of a sample, for example, the algorithm works by summing all the data values observed in the sample and then dividing this sum by the number of data items. This single measure, the mean of the sample, is called a statistic; its value is frequently used as an estimate of the mean value of all items comprising the population from which the sample is drawn.
The population mean is also a single measure; however, it is not called a statistic, because it is not obtained from a sample; instead it is called a population parameter, because it is obtained from the whole population. A statistic is an observable random variable , which differentiates it both from a parameter that is a generally unobservable quantity describing a property of a statistical population , and from an unobservable random variable, such as the difference between an observed measurement and a population average.
A parameter can only be computed exactly if entire population can be observed without error; for instance, in a perfect census or for a population of standardized test takers. Statisticians often contemplate a parameterized family of probability distributions , any member of which could be the distribution of some measurable aspect of each member of a population, from which a sample is drawn randomly.
For example, the parameter may be the average height of year-old men in North America. See all condition definitions - opens in a new window or tab Read more about the condition.
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