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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. Robust statistics - Wikipedia

    en.wikipedia.org/wiki/Robust_statistics

    First, an outlier detection method that relies on a non-robust initial fit can suffer from the effect of masking, that is, a group of outliers can mask each other and escape detection. [17] Second, if a high breakdown initial fit is used for outlier detection, the follow-up analysis might inherit some of the inefficiencies of the initial estimator.

  4. Z-factor - Wikipedia

    en.wikipedia.org/wiki/Z-factor

    Note that by the standards of many types of experiments, a zero Z-factor would suggest a large effect size, rather than a borderline useless result as suggested above. For example, if σ p =σ n =1, then μ p =6 and μ n =0 gives a zero Z-factor.

  5. 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]

  6. Little Professor - Wikipedia

    en.wikipedia.org/wiki/Little_Professor

    As the first electronic educational toy, [6] [7] the Little Professor is a common item on calculator collectors' lists. [8] In 1976, the Little Professor cost less than $20. More than 1 million units sold in 1977. [9]

  7. Trimmed estimator - Wikipedia

    en.wikipedia.org/wiki/Trimmed_estimator

    In statistics, a trimmed estimator is an estimator derived from another estimator by excluding some of the extreme values, a process called truncation.This is generally done to obtain a more robust statistic, and the extreme values are considered outliers. [1]

  8. 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 ...

  9. Taguchi methods - Wikipedia

    en.wikipedia.org/wiki/Taguchi_methods

    Taguchi methods (Japanese: タグチメソッド) are statistical methods, sometimes called robust design methods, developed by Genichi Taguchi to improve the quality of manufactured goods, and more recently also applied to engineering, [1] biotechnology, [2] [3] marketing and advertising. [4]