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  2. Failure rate - Wikipedia

    en.wikipedia.org/wiki/Failure_rate

    The Failures In Time (FIT) rate of a device is the number of failures that can be expected in one billion (10 9) device-hours of operation [17] (e.g. 1,000 devices for 1,000,000 hours, or 1,000,000 devices for 1,000 hours each, or some other combination).

  3. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In the empirical sciences, the so-called three-sigma rule of thumb (or 3 σ rule) expresses a conventional heuristic that nearly all values are taken to lie within three standard deviations of the mean, and thus it is empirically useful to treat 99.7% probability as near certainty.

  4. Mean time between failures - Wikipedia

    en.wikipedia.org/wiki/Mean_time_between_failures

    where B 10 is the number of operations that a device will operate prior to 10% of a sample of those devices would fail and n op is number of operations. B 10d is the same calculation, but where 10% of the sample would fail to danger. n op is the number of operations/cycle in one year. [11]

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable.The general form of its probability density function is [2] [3] = ().

  6. First-pass yield - Wikipedia

    en.wikipedia.org/wiki/First-pass_yield

    In this case, 70/100 = 0.70 or 70% yield. The same example using first pass yield (FPY) would take into account rework: (# units leaving process A as good parts with no rework) / (# units put into the process) 100 units enter process A, 5 were reworked, and 90 leave as good parts. The FPY for process A is (90-5)/100 = 85/100 = 0.8500

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  8. Statistical theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_theory

    The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.

  9. Fractional factorial design - Wikipedia

    en.wikipedia.org/wiki/Fractional_factorial_design

    Each generator halves the number of runs required. A design with p such generators is a 1/(l p)=l −p fraction of the full factorial design. [3] For example, a 2 52 design is 1/4 of a two-level, five-factor factorial design. Rather than the 32 runs that would be required for the full 2 5 factorial experiment, this experiment requires only ...