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  • Hayter, Anthony J.  (2)
  • Biodiversity Research  (2)
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  • Biodiversity Research  (2)
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  • 1
    Online Resource
    Online Resource
    Wiley ; 2015
    In:  Biometrical Journal Vol. 57, No. 1 ( 2015-01), p. 52-63
    In: Biometrical Journal, Wiley, Vol. 57, No. 1 ( 2015-01), p. 52-63
    Abstract: Normal probability plots are widely used as a statistical tool for assessing whether an observed simple random sample is drawn from a normally distributed population. The users, however, have to judge subjectively, if no objective rule is provided, whether the plotted points fall close to a straight line. In this paper, we focus on how a normal probability plot can be augmented by intervals for all the points so that, if the population distribution is normal, then all the points should fall into the corresponding intervals simultaneously with probability . These simultaneous probability intervals provide therefore an objective mean to judge whether the plotted points fall close to the straight line: the plotted points fall close to the straight line if and only if all the points fall into the corresponding intervals. The powers of several normal probability plot based (graphical) tests and the most popular nongraphical Anderson‐Darling and Shapiro‐Wilk tests are compared by simulation. Based on this comparison, recommendations are given in Section 3 on which graphical tests should be used in what circumstances. An example is provided to illustrate the methods.
    Type of Medium: Online Resource
    ISSN: 0323-3847 , 1521-4036
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 131640-0
    detail.hit.zdb_id: 1479920-0
    SSG: 12
    Location Call Number Limitation Availability
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2013
    In:  Biometrical Journal Vol. 55, No. 3 ( 2013-05), p. 360-369
    In: Biometrical Journal, Wiley, Vol. 55, No. 3 ( 2013-05), p. 360-369
    Abstract: A common statistical problem is to make inference about the mean of a normally distributed population. While the mean and the variance are important quantities, many real problems require information on certain quantiles of the population which combine both the mean and variance. Motivated by two recent applications, we consider simultaneous inference for more than one quantile of interest. In this paper, a set of exact level simultaneous confidence intervals for several quantiles of a normally distributed population is constructed, based on a simple random sample from that population. The critical constants for achieving an exact simultaneous coverage probability can be computed efficiently using numerical quadrature involving only a one‐dimensional integral combined with standard search algorithms. The proposed methods are illustrated with an example. Several further research problems are identified.
    Type of Medium: Online Resource
    ISSN: 0323-3847 , 1521-4036
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2013
    detail.hit.zdb_id: 131640-0
    detail.hit.zdb_id: 1479920-0
    SSG: 12
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
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