Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach

By Gregory W. Corder, D. Foreman. 2009

1,304 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/2dd7c4a7d50f807541d0069cb23a43a8a0b8bafc

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In Statistics and Probability

1. A. Raccanelli
2. Rong Jin
3. C. Baeza
4. Lin Tan
5. L. Rivera
6. Antanas Verikas
7. Tim Menzies
8. Sunghun Kim

Citations in the corpus

• Spin models inferred from patient-derived viral sequence data faithfully describe HIV fitness landscapes (2013, positive): “A Spearman rank test [25] shows that the order of ranking is preserved with very high statistical accuracy for most strains (ρ = 0.”
• Interpreting large-scale redshift-space distortion measurements (2011, methodology): “We perform a Kolmogorov-Smirnov test (for detailed discussion of the test see, e.g., Corder & Foreman (2009)) to see if the empirical distribution of ξℓ measurements is consistent with the null hypothesis that they are drawn from a Gaussian distribution.”
• Mining data with random forests: A survey and results of new tests (2011, methodology): “Spearman correlation between the Gini index-based variable importance and the variable importance evaluated with the Mann-Whitney U test [98] for the top 35 variables (out of 57) was highly significant ðr1⁄4 0:764,po0:0001Þ.”
• Heterogeneous Defect Prediction (2015, methodology): “05 which is one of commonly accepted significance levels in the statistical test [91].”
• Statistical and spatial analysis of landslide susceptibility maps with different classification systems (2016, background): “First of all, a nonparametric measure of statistical dependence between ranked variables (normality and homogeneity of variance assumptions are not satisfied) was calculated (Corder and Foreman 2009).”
• Regularized Distance Metric Learning: Theory and Algorithm (2009, methodology): “To further verify if the proposed method performs statistically better than the baseline methods, we conduct statistical test by using Wilcoxon signed-rank test [3].”
• Logistics agglomeration in the US (2014, positive): “Cooper and Schindler, 2003) and can be used when it cannot be assumed that the dependent variable is normally distributed (it is only assumed that the variable is ordinal). Several studies have applied the Wilcoxon rank sum test (WRST) to compare the distribution of different responses or validate t”