Apple Inc. faces risks in a high P/E market with large debt exposure, predicting a -6.5% dip in downturns. Click for our ...

Multiple linear regression was performed using the items selected ... The relationship between the Nancy index and GVE was investigated using the Pearson correlation coefficient; a coefficient >0.8 ...

And multiple linear regression was also used to predict depression SDS ... and migraines, with the largest correlation coefficient for anxiety (Spearman’s rho = 0.531). However, no significant ...

Objective Disease activity both between and within patients with SLE is highly variable, yet factors driving this variability remain unclear. This study aimed to identify predictors of variability in ...

Figure 1. The CODA-LASSO approach extends the linear regression approach by taking log abundances of microbiome data and considering two additional constraints. Constraint 1 is the LASSO constraint ...

Reproducibility data are expressed as the coefficient of variation (CV) = standard deviation/mean. The correlation between RNFL/retinal thickness and age is presented as a linear regression together ...

(Optional) Click on "Generate charts of spectral indices vs Landsat LST" to generate scatterplots of correlation ... the linear regression model between LSTL8 and the spectral indices NDVIL8, NDBIL8, ...

Cox regression and restricted cubic spline models and polygenic ... to address the potential issue of collinearity among lipid fractions, we calculated Pearson correlation coefficients and conducted ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random neighborhoods ...

Heliot Ramos, Tyler Fitzgerald and the Giants' propensity for getting on base to start an inning are due for regressions.

Many studies have used single-cell RNA sequencing (scRNA-seq) to infer gene regulatory networks (GRNs), which are crucial for ...