Theorem 6 There is no complete correlation between the time correlation indicator and completeness indicator.
(The scale runs from 1, for complete correlation, to negative 1, implying an inverse relationship).
Researchers use what they call a correlation coefficient, a number that ranges from "+1," meaning that the two assets have perfect, or complete, correlation, to "-1," meaning that they have perfect inverse correlation.
[Correction: This paragraph initially stated that an r-squared of 100% means complete correlation, a score of -100% is perfect inverse correlation, and a score of 0% means no link either way. That is true of the correlation coefficient. The r-squared term is the square of the correlation coefficient.] My own data crunching gives 63%; I think it takes academic data from different years.
The complete correlation matrix is depicted in Table 10.
For the animals inoculated with 1 × 106 CFU of bacteria, there was complete correlation between radiographic, microbiological and molecular testing.
A requirement for the feasibility of multivariate meta-analysis is the estimation of the complete correlation matrix between the proxy variables and the hedging dummy.
Table 1 presents descriptive statistics of all variables included in our analysis (see also Appendix Table 5 for the complete correlation matrix).
Most traits measured in hydroponics correlated with herbicide score, but the correlations were strongest with root traits (see Additional file 9: Table S6 for complete correlation data).
In conclusion, there is not a complete correlation between data volume indicator and correctness indicator, which can be described as ( {q}_voverset{sim }{prec }{q}_t ) ■. Theorem 3 The data volume indicator and the correctness indicator are not completely correlated.
In particular we show that, in contrast to the PME, the dichotomous Gaussian model gives a highly accurate description of the complete correlation structure of an integrate-and-fire population with common inputs.
