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X bar, x̄ (or X̄) or X-bar may refer to: X-bar theory, a component of linguistic theory; Arithmetic mean, a commonly used type of average; An X-bar, a rollover protection structure; Roman numeral 10,000 in vinculum form
The arithmetic mean of a series of values ,, …, is often denoted by placing an "overbar" over the symbol, e.g. ¯, pronounced "bar". Some commonly used symbols for sample statistics are given below: the sample mean ¯,
The arithmetic mean is often denoted by a bar (vinculum or macron), as in ¯. [4] Some software (text processors, web browsers) may not display the "x̄" symbol correctly. For example, the HTML symbol "x̄" combines two codes — the base letter "x" plus a code for the line above ( ̄ or ¯). [8]
¯ ¯ ¯ for monitoring the process mean where x ¯ ¯ {\displaystyle {\bar {\bar {x}}}} and R ¯ {\displaystyle {\bar {R}}} are the estimates of the long-term process mean and range established during control-chart setup and A 2 , D 3 , and D 4 are sample size-specific anti-biasing constants.
The arithmetic mean (or simply mean or average) of a list of numbers, is the sum of all of the numbers divided by their count. Similarly, the mean of a sample x 1 , x 2 , … , x n {\displaystyle x_{1},x_{2},\ldots ,x_{n}} , usually denoted by x ¯ {\displaystyle {\bar {x}}} , is the sum of the sampled values divided by the number of items in ...
The arithmetic mean of a population, or population mean, is often denoted μ. [2] The sample mean ¯ (the arithmetic mean of a sample of values drawn from the population) makes a good estimator of the population mean, as its expected value is equal to the population mean (that is, it is an unbiased estimator).
In industrial statistics, the X-bar chart is a type of variable control chart [1] that is used to monitor the arithmetic means of successive samples of constant size, n. This type of control chart is used for characteristics that can be measured on a continuous scale, such as weight, temperature, thickness etc.
¯ = sample mean of differences d 0 {\displaystyle d_{0}} = hypothesized population mean difference s d {\displaystyle s_{d}} = standard deviation of differences