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  2. Free Sample of Depends - AOL

    www.aol.com/2010/11/22/free-sample-of-depends

    Get a free - and discreet - sample of Depends underwear for adults through the mail when you share your name, address, email, date of birth and gender. You can choose to receive a sample pack for ...

  3. Depend (undergarment) - Wikipedia

    en.wikipedia.org/wiki/Depend_(undergarment)

    Depend (undergarment) Depend is a Kimberly-Clark brand of absorbent, disposable undergarments for people with urinary or fecal incontinence. It positions its products as an alternative to typical adult diapers. Depend is the dominant brand of disposable incontinence garments in the United States with a 49.4 share of the market.

  4. Sampling distribution - Wikipedia

    en.wikipedia.org/wiki/Sampling_distribution

    Introduction. The sampling distribution of a statistic is the distribution of that statistic, considered as a random variable, when derived from a random sample of size . It may be considered as the distribution of the statistic for all possible samples from the same population of a given sample size. The sampling distribution depends on the ...

  5. Brooklyn Decker: I'm at the ‘Depends-Wearing Stage ... - AOL

    www.aol.com/entertainment/brooklyn-decker-im...

    Brooklyn Decker let her Instagram followers in on a personal phase she’s embarked on in her menstrual cycle. Read article. On Sunday, July 19, the 33-year-old Just Go With It actress flashed a ...

  6. Sample entropy - Wikipedia

    en.wikipedia.org/wiki/Sample_entropy

    Sample entropy. Sample entropy (SampEn) is a modification of approximate entropy (ApEn), used for assessing the complexity of physiological time-series signals, diagnosing diseased states. [1] SampEn has two advantages over ApEn: data length independence and a relatively trouble-free implementation. Also, there is a small computational ...

  7. Bias of an estimator - Wikipedia

    en.wikipedia.org/wiki/Bias_of_an_estimator

    Bias of an estimator. In statistics, the bias of an estimator (or bias function) is the difference between this estimator 's expected value and the true value of the parameter being estimated. An estimator or decision rule with zero bias is called unbiased. In statistics, "bias" is an objective property of an estimator.

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