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r - Interpretation when converting correlation of continuous data to Cohen's d - Cross Validated

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A popular textbook on meta-analysis (1) discusses how to convert a correlation, $r$, to Cohen's $d$ (i.e., the standardized mean difference): I became confused about how to interpret the resulting

R Handbook: Correlation and Linear Regression

Pearson correlation coefficient - Wikipedia

Pearson correlation coefficient - Wikipedia

Clinical and technical outcomes of robotic versus manual percutaneous coronary intervention: A systematic review and meta-analysis - ScienceDirect

regression - Is this a correct interpretation of the r correlation coefficient - Cross Validated

At-home wearables and machine learning sensitively capture disease progression in amyotrophic lateral sclerosis

Impact of air pollutants on climate change and prediction of air quality index using machine learning models - ScienceDirect

Diagnostics, Free Full-Text

An overview of correlation measures between categorical and continuous variables, by Outside Two Standard Deviations

3.3. Metrics and scoring: quantifying the quality of predictions — scikit-learn 1.4.1 documentation

3.3. Metrics and scoring: quantifying the quality of predictions — scikit-learn 1.4.1 documentation

Chapter 48 Applying k-Fold Cross-Validation to Logistic Regression