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--- nlp:experimental_method [2022/10/07 16:46] – [Statistical Significance] brendan
+++ nlp:experimental_method [2023/06/15 07:36] (current) – external edit 127.0.0.1
@@ Line 24: / Line 24: @@
   * [[https://aclanthology.org/P19-1266.pdf|Dror et al 2019 - Deep Dominance - How to Properly Compare Deep Neural Models]] Caveat: some researchers have advocated tuning the random seed as a hyperparameter, see [[nlp:experimental_method#Effects of the Random Seed]]
   * [[https://arxiv.org/pdf/2204.06815.pdf|Ulmer et al 2022 - Deep-Significance - Easy and Meaningful Statistical Significance Testing in the Age of Neural Networks]]
-  * [[https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.wilcoxon.html|Sign Test Docs in SciPy]]. An issue to consider is how to include outcomes in which system A & B produce the same prediction/score. See the ''zero_method'' parameter and associated links.
+  * [[https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.wilcoxon.html|Wilcoxon Signed-Rank Test Docs in SciPy]]. An issue to consider is how to include outcomes in which system A & B produce the same prediction/score. See the ''zero_method'' parameter and associated links.
 ==== Boostrap Resampling and Permutation Tests ====