File:Pearson correlation and prediction intervals.svg
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Summary
| Description |
English: This figure gives a sense of how the usefulness of a Pearson correlation for predicting values varies with its magnitude. Given jointly normal X, Y with correlation ρ, (plotted here as a function of ρ) is the factor by which a given prediction interval for Y may be reduced given the corresponding value of X. For example, if ρ = .5, then the 95% prediction interval of Y|X will be about 13% smaller than the 95% prediction interval of Y.
The formula coincides with the "forecasting efficiency" value E defined by: Hull, C. L. (1927). The correlation coefficient and its prognostic significance. Journal of Educational Research, 15, 327–338. Retrieved from https://www.jstor.org/stable/27523485 |
| Date | |
| Source | Own work |
| Author | Kodi Arfer |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 15:04, 21 March 2013 | | 956 × 670 (49 KB) | Kodiologist | User created page with UploadWizard |
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