Sentence examples for multiple regression of from inspiring English sources

Unfortunately, their multiple regression of potential predictive variables cannot be interpreted reliably.

A model was obtained for each response by linear multiple regression of a second-degree mathematical expression.

The confusion matrices considered here are from phenotypic data (PHEN) and from the spatial multiple regression of fMRI resting state (SMR2, SMR5, SMR7).

We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace.

Spatial correlation was evaluated using Mantel tests and correlograms and multiple regression of distance matrices within causal modeling and relative support frameworks.

The r-value from multiple regression of degree of starch access (DSA) on DM content and mean particle size for HMC was 0.78 (P < 0.0001).

Multiple regression of flow discharge against rainfall and temperature was used to determine the residual trend at four meteorological and hydrological stations located upstream and downstream of the Qom Rood Watershed.

It is proposed to estimate the log speech spectrum at a hypothetical close-talking microphone that should have good quality by multiple regression of the log spectra of several distant microphone signals.

Table 2 Multiple regression of predictor variables for L2 listening proficiency Criterion variable β t p VIF External Regulation −.063 −1.019.274 1.019 Introjected Regulation −.118 −1.246.061 1.246 Identified Regulation.075.984.326 1.827 Intrinsic Motivation.207 3.655.000*** 1.000 Note.

Multiple regression of yield on rainfall and dd indicates that only rainfall was a significant predictor of yield at Yavatmal that averaged 521kg lint cotton ha−1 (SD = +212.1) (Fig. 4b; Eq. 1).

Multiple regression of average rainfed yields (data from Fig. 6a) on total degree days during the growing season (dd > 12 °C, t = 7.34), rainfall (t = −13.83), and the interaction term dd × rainfall (t = 35.12) is summarized by Eq. 2.