A wide variety of standard statistical performance evaluation measures are needed to properly evaluate the performances of various ANN models rather than relying on a few global error statistics (such as RMSE and correlation coefficient) normally employed.
Cronbach's α reliability coefficient normally ranges between 0 and 1.
Associations of prepregnancy SHBG levels with prepregnancy BMI, age, and glucose, insulin, cholesterol, and HOMA-IR levels were estimated with Pearson correlation coefficients for normally distributed variables and Spearman correlation coefficients for non-normally distributed variables.
Correlations were calculated using Pearson correlation coefficients for normally distributed values and Spearman correlation coefficients when normality was rejected.
Since such coefficients are normally sparse (only few coefficients are nonzero) or compressible (decaying rapidly according to power law), the compression (e.g., image compression in JEPG2000 [3]) can be achieved via storing and transmitting the nonzero coefficients.
Statistical significance of coexpression was assessed based on the approximation that Fisher's z-transformed correlation coefficients are normally distributed with standard error of (N-3)−1/2 [30].
Fisher's z transform converts correlation coefficients
Ninety-five perconfidencedence intervals (CIs) of the RRs were obtained under the assumption that the estimated regression coefficients were normally distributed.
The cepstral coefficients are normally calculated via one of the following two pre-processing routes: linear predictive coding (LPC) or a bank-of-filters front-end processor [26, 31, 32].
