<unk>  is a branch of statistics which deals with death in biological organisms and failure in mechanical systems. 
This topic is called reliability theory or reliability analysis in engineering, and duration analysis or duration modeling in economics or sociology.
More generally,<unk>  involves the modelling of time to event data; in this context, death or failure is considered an "event" in the<unk>  literature. Another example of time to event modeling could be the rate or time to which former convicts commit a crime again after they've been released. In this case, the 'event' of interest would be time to committing a crime. Many concepts in<unk>  have been explained by the Counting Process Theory, which has emerged more recently. The flexibility of a counting process is that it allows modeling multiple (or recurrent) events. This type of modeling fits very well in many situations (e.g. people can go to jail multiple times, alcoholics can start and stop drinking multiple times, people can get married and get a divorce many times).<unk>  attempts to answer questions such as: what is the fraction of a population which will survive past a certain time? Of those that survive, at what rate will they die or fail? Can multiple causes of death or failure be taken into account? How do particular circumstances or characteristics increase or decrease the odds of<unk> ?
To answer such questions, 
it is necessary to define "lifetime".
In the case of biological<unk> ,
death is unambiguous,
but for mechanical reliability,
failure may not be well-defined,
for there may well be mechanical systems in which failure is partial, a matter of degree, or not otherwise localized in time.
Even in biological problems,
some events (for example, heart attack or other organ failure) may have the same ambiguity.
The theory outlined below assumes well-defined events at specific times;
other cases may be better treated by models which explicitly account for ambiguous events.
The theory of<unk>  presented here also assumes that death or failure happens just once for each subject.
Recurring event or repeated event models relax that assumption.
The study of recurring events is relevant in systems reliability, and in many areas of social sciences and medical research.
This article is phrased primarily in terms of biological<unk> , 
but this is just a convenience.
An equivalent formulation in terms of mechanical failure can be made by replacing every occurrence of death with failure.
Survival analysis
Cost-effectiveness analysis
Multivariate analysis
Proportional hazards models
Meta-analysis
Receiver operating characteristic
Intention to treat analysis
Agent study