Similar age patterns were found for all-cause deaths; the correlation coefficient between respiratory and all-cause excess-death rates was >0.99 (p<0.01).
This causes a drop in the correlation coefficient.
The correlation coefficient was analyzed using Pearson's correlation coefficient.
The correlation coefficient, r, measures the extent of the correlation between two variables.
The mathematical tools he invented -- regression and the correlation coefficient -- are also used universally today.
The correlation coefficient is calculated according to equation (1).
The correlation coefficient values are shown in Table 3.
Pearson's correlation coefficient was used to calculate associations between variables with p < 0.05, indicating significance of the correlation coefficient.
The correct assignment showed a higher correlation coefficient, indicating that the correlation coefficient can be reliably used as a score to discriminate correct from incorrect assignments (the significance of the difference between the correlation coefficients is p = 0.00017).
The correlation coefficient between 51Cr-EDTA-clearance and 1/cystatin C was 0.72 compared to the correlation coefficient between 51Cr-EDTA-clearance and 1/creatinine being 0.26.
