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  2. Robust parameter design - Wikipedia

    en.wikipedia.org/wiki/Robust_parameter_design

    Robust parameter designs use a naming convention similar to that of FFDs. A 2 (m1+m2)-(p1-p2) is a 2-level design where m1 is the number of control factors, m2 is the number of noise factors, p1 is the level of fractionation for control factors, and p2 is the level of fractionation for noise factors. Effect sparsity.

  3. Time constant - Wikipedia

    en.wikipedia.org/wiki/Time_constant

    First order LTI systems are characterized by the differential equation + = where τ represents the exponential decay constant and V is a function of time t = (). The right-hand side is the forcing function f(t) describing an external driving function of time, which can be regarded as the system input, to which V(t) is the response, or system output.

  4. Robust statistics - Wikipedia

    en.wikipedia.org/wiki/Robust_statistics

    Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers .

  5. Why some parents are committing to spending 1,000 hours ... - AOL

    www.aol.com/lifestyle/why-parents-committing...

    Kids between 8 and 18 spend an average of 7.5 hours in front of a screen — every day, according to the Centers for Disease Control and Prevention. It’s probably not the most shocking statistic ...

  6. Robust measures of scale - Wikipedia

    en.wikipedia.org/wiki/Robust_measures_of_scale

    Robust measures of scale can be used as estimators of properties of the population, either for parameter estimation or as estimators of their own expected value.. For example, robust estimators of scale are used to estimate the population standard deviation, generally by multiplying by a scale factor to make it an unbiased consistent estimator; see scale parameter: estimation.

  7. Generalized estimating equation - Wikipedia

    en.wikipedia.org/wiki/Generalized_estimating...

    GEE estimates the average response over the population ("population-averaged" effects) with Liang-Zeger standard errors, and in individuals using Huber-White standard errors, also known as "robust standard error" or "sandwich variance" estimates. [3]

  8. 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).

  9. Z-factor - Wikipedia

    en.wikipedia.org/wiki/Z-factor

    The Z-factor is a measure of statistical effect size. It has been proposed for use in high-throughput screening (HTS), where it is also known as Z-prime, [ 1 ] to judge whether the response in a particular assay is large enough to warrant further attention.