The probability that a given active maintenance action, for an item under given conditions of use can be carried out within a stated time interval, when the maintenance is performed under stated conditions and using stated procedures and resources. [4: 191-13-01]

The expected value of a random variable. [1: 1.18].

The arithmetic mean of the deviations from an origin when all deviations are given a positive sign. Note: Generally, the chosen origin is the arithmetic mean, although the mean deviation is minimized by taking the median as the origin. [1: 2.32].

The arithmetic mean of the times-to-failure of the units of a given item.

The total preventive and corrective maintenance time divided by the total number of preventive and corrective maintenance actions during a specified period of time. [7]

The expectation of the number of services completed in one time unit, given that service is going throughout the entire time unit.

The expectation of the time between failures. [4: 191-12-08]

The expectation of the time to failure. [4: 191-12-07]

The expectation of the time to restoration. [4: 191-13-08]

If n values are arranged in non-decreasing order of magnitude and numbered 1 to n, the median of these n values is the [(n + 1)/2]th and value, if n is odd. If n is even, the median lies between the (n/2)th and the [(n/2) + 1]th values and is not defined uniquely. Unless otherwise specified, it may be taken to be the arithmetic mean of these two values.[1: 2.28].

Noting the presence (or absence) of some characteristic or attribute in each of the items in the group under consideration, and counting how many items do (or do not) possess the attribute, or how many such events occur in the item, group, or area. Note: One of the most common attribute measures for acceptance sampling is the percentage of nonconforming items. [2: 1.52]

The arithmetic mean of the largest and the smallest observed value of a quantitative characteristic. [1: 2.29].

The value(s) of a random variable such that the probability mass (discrete random variable) or the probability density (continuous random variable) has a local maximum for this value (or these values). Note: If there is one mode, the probability distribution of the random variable is said to be "unimodal"; if there is more than one mode the probability distribution is said to be "multimodal" (bimodal if there are two modes.) [1: 1.17].

An unweighted average of the latest n observations where the current observations has replaced the oldest of the previous n observations. [2: 3.3.18].

A control chart for evaluating process level in terms of an arithmetic average of the latest n observations in which the current observation has replaced the oldest of the latest n + 1 observations. [2: 3.3.18].

A control chart for evaluating the variability within a process in terms of the range of the latest n observations in which the current observation has replaced the oldest of the latest n + 1 observations.[ 2: 3.3.20].

Sampling inspection in which, after each sample has been inspected, a decision is made, based upon defined rules, to accept the lot, not to accept it, or to take another sample. The decision rules are based on the cumulative evidence of all the samples from that lot. Note: For most multiple sampling plans, the largest number of samples that can be taken is specified with an "accept" or "not accept" decision being forced at that point. [2: 2.4.3]

A control chart for evaluating a process in terms of the levels of two or more characteristics. [2: 3.3.23].