A statistic (singular) is the result of applying a statistical algorithm to a set of data. In the calculation of the arithmetic mean, for example, the algorithm directs us to sum all the data values and divide by the number of data items. In this case, we call the mean a statistic. To be complete in describing any use of a statistic, one must describe both the procedure and the data set. Flowcharts are often used to represent algorithms. ... In statistics, a data set is a set of data consisting of: a list of research subjects and the data vector associated with each. ... In mathematics and statistics, the arithmetic mean of a set of numbers is the sum of all the members of the set divided by the number of items in the set (cardinality). ... Data is the plural of datum. ...
The popular use of the term to mean a single measurement, or datum, differs from this meaning. A statistician would normally call an individual person's height a statistic only if that person were chosen randomly from some population of interest, but more often would use the term to refer to, for example, the median height of a group of people. It has been suggested that this article or section be merged with Geodetic system. ... In probability theory and statistics, the median is a number that separates the higher half of a sample, a population, or a probability distribution from the lower half. ...
Often the concept is defined by saying that a statistic is an observablerandom variable. Statisticians often contemplate a parametrized family of probability distributions, any member of which could be the distribution of some measurable aspect of each member of a statistical population from which a sample is drawn randomly. The value of the parameter is not observable, since it depends on the whole population rather than on the sample. For example, the parameter may be the average height of 25-year-old men in North America. The height of the members of a sample of 100 such men are measured; the average of those 100 numbers is a statistic; the average of the heights of all members of the population is not a statistic (unless that has somehow also been ascertained). The difference between that observable sample average and the unobservable population average is an example of a random variable that is not a statistic; the reason it is random is that the sample was chosen randomly. A random variable is a term used in mathematics and statistics. ... In mathematics, a probability distribution assigns to every interval of the real numbers a probability, so that the probability axioms are satisfied. ... In statistics, a statistical population is a set of entities concerning which statistical inferences are to be drawn, often based on a random sample taken from the population. ...
not much. i hate statistics we'll get kicked out of wikipedia i doubt it. We'll just go to another page or something. A graph of a bell curve in a normal distribution showing statistics used in educational assessment, comparing various grading methods. ... The theory of statistics includes a number of topics: Statistical models of the sources of data and typical problem formulation: Sampling from a finite population Measuring observational error and refining procedures Studying statistical relations Planning statistical research to measure and control observational error: Design of experiments to determine treatment effects...
To understand these statistics, it is necessary to know how overweight and obesity are defined and measured, something this publication addresses.
For age-adjusted rates, statisticalprocedures are used to remove the effect of age differences when comparing two or more populations at one point in time, or one population at two or more points in time.
Most of the statistics presented here represent the economic cost of overweight and obesity in the United States in 1995, updated to 2001 dollars.[10] Unless otherwise noted, these statistics are adapted from Wolf and Colditz,[11] who based their data on existing epidemiological studies that defined overweight and obesity as a BMI > 29.
Simple forms of statistics have been used since the beginning of civilization, when pictorial representations or other symbols were used to record numbers of people, animals, and inanimate objects on skins, slabs, or sticks of wood and the walls of caves.
Registration of deaths and births was begun in England in the early 16th century, and in 1662 the first noteworthy statistical study of population, Observations on the London Bills of Mortality, was written.
At present, statistics is a reliable means of describing accurately the values of economic, political, social, psychological, biological, and physical data and serves as a tool to correlate and analyze such data.
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