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Updated: Jun 14, 2025

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

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在空间扫描统计中负二项式-GLM的性能:巴基斯坦低出生体重的案例研究

Sami Ullah1, Mushtaq Ahmad Khan Barakzai2, Tianfa Xie3

  • 1School of Mathematics, Statistics and Mechanics, Beijing University of Technology. sami.khan3891@gmail.com.

Geospatial health
|September 4, 2024
PubMed
概括

负二项式通用线性模型 (GLM) 是理想的空间扫描统计数据与过度分散的健康数据. 这种方法有效地发现了巴基斯坦的低出生体重集群,表现优于Poisson GLM和GLMM.

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Scanning Skeletal Remains for Bone Mineral Density in Forensic Contexts

Published on: January 29, 2018

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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
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A complete procedure of testing the hypothesis about a population mean is explained here.
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z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
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Sign Test for Matched Pairs01:17

Sign Test for Matched Pairs

The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
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Introduction to Nonparametric Statistics01:28

Introduction to Nonparametric Statistics

Nonparametric statistics offer a powerful alternative to traditional parametric methods, useful when assumptions about the population distribution cannot be made. Unlike parametric tests, which require data to follow a specific distribution with well-defined parameters (such as the mean and standard deviation), nonparametric tests do not require such constraints. This makes them particularly valuable when dealing with small sample sizes, skewed data, or ordinal and categorical variables.
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