Pearsons r Solar Influence on Indian Ocean
The variables examined in this study were H5 which is a stalagmite from Hoti cave (southern Oman) that grew in early Holocene. The oxygen isotopic composition (Î´ 18 O) of the speleothem is primarily determined by the Î´ 18 O of drip water and, hence, the Î´ 18 O of precipitation which is controlled by Indian Ocean monsoon intensity via an amount effect (Mudelsee, 2003).
In this study, Pearsons correlation coefficient if estimated to be r = 0.6. The Pearson coefficient r represents the linear relationship between the two used variables. The H5 Î´ 18 O record serves as indicator of Holocene monsoon rainfall (low Î´ 18 O reï¬‚ects strong rainfall).If the r is squared then resulting r2 will rep the proportion or common variation in the two variables i.e. magnitude of the relationship.
Confidence intervals were reported for the study. Confidence intervals were [0.51; 0.66], with 95% BCa. Monte Carlo simulations reveal that taking positive serial dependence (persistence) into account is essential for obtaining accurate confidence intervals (of type bootstrap BCa) for Pearsons correlation coefficient from bivariate climate time series data (Mudelsee, 2003). Confidence intervals are designed for use with classification problems by combating over-learning and improve generalization as well as report the average performance and error measures of their member networks.
An effective data size, n â‰³200 for max (Ï„x , Ï„ y ) = 2d, n â‰³500 1000 for max(Ï„x , Ï„ y ) = 5d. This means that with positive serial dependence, more data is needed than when no persistence is in the data for achieving an accuracy of the conï¬dence interval that is acceptable in geosciences.
Mudelsee M. (2003). Estimating Pearsons correlation coefficient with Bootstrap confidence interval from serially dependent time series. Mathematical Geology, Vol. 35, No. 6, pp 659- 662.
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