VII. Note on regression and inheritance in the case of two parents

By K. Pearson

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From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline (2024, neutral): “Statistical measures like Pearson [33] and Spearman Correlations, commonly used in benchmarks such as AlpacaEval [25] to measure correlation to human preference ranking, may fail to adequately address model separability and ranking instability.”
Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features (2017, methodology): “These similarity scores are compared to the gold-standard human judgements using Pearson’s r (Pearson, 1895) and Spearman’s ρ (Spearman, 1904) correlation scores.”
Standing on the Shoulders of Dwarfs: the Kepler Asteroseismic LEGACY Sample. I. Oscillation Mode Parameters (2016, methodology): “Correlations have been estimated using Spearman’s rank correlation (Spearman 1904) from the MCMC chains, because this better catches dependencies which are monotonic but not necessarily linear (as done in Pearson’s correlation; Pearson 1895).”
The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks (2020, background): “, accuracy) [2, 15]; (2) in the BSC, Pearson’s Correlation Coefficient r [16], because the target variable is interval-scaled.”
Knowledge-based Systems (2009, unknown): “We now study the aggregation of value systems for the European Values Study case.”
CharacTer: Translation Edit Rate on Character Level (2016, methodology): “Currently the most common techniques for calculating the correlation between human and automatic evaluations are the Spearman’s rank correlation coefficient (Spearman, 1904) and the Pearson product-moment correlation coefficient (Pearson, 1895).”
A Novel NLOS Mitigation Algorithm for UWB Localization in Harsh Indoor Environments (2019, methodology): “To select an optimal subset from the eight features, we use the PCC analysis method to calculate the correlations between different features [37].”
Forming Core Collections in Barnyard, Kodo, and Little Millets using Morphoagronomic Descriptors (2014, background): “org 2675 diversity index (H ́) (Shannon and Weaver, 1949); the correlation coefficients (Pearson, 1895); the coincidence rate (CR%), and the variable rate (VR%) (Hu et al.”
Measuring user influence on Twitter: A survey (2015, methodology): “Other known coeﬃcients are the Pearson correlation coeﬃcient [100] and the Goodman-Kruksal gamma [48].”