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Accelerated life Testing
A set of methods or techniques which are intended to ensure product reliability during the time of design and manufacture in which stress is applied to promote the failure. The applied stresses might be vibration, temperature, shock etc. In order to make a valid inference about the normal lifetimeof the system from the accelerated data (accelerated in the sense that a shortened time to the failure is implied), it is essential to know the association between time to failure and applied stress. Frequently parametric statistical models of the time to failure and of the manner in which the stress accelerates aging are used.
O. J. Simpson paradox is a term coming from the claim made by the defence lawyer in murder trial of O. J. Simpson. The lawyer acknowledged that the statistics demonstrate that onl
Ask quesoil company is considering whether or not to bid for an offshore drilling contract. If they bid, the value would be $600m with a 65% chance of gaining the contract. The com
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic
How to estimate MLE for statistical anslysis using Markov Model?
An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is oil in the ground, the soil test comes
Attack rate : This term frequently used for the incidence of the disease or condition in the particular group, or during a limited interval of time, or under the special circumstan
High-dimensional data : This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21 st
Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent
Johnson''s Job Sequencing for n jobs and 2 machines
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