Sentence examples for multiple regression showed from inspiring English sources

Multiple regression showed that base morpheme frequency and family size were independent predictors of response times to derived words.

Both calibration techniques enhanced the accuracy of the models, however nonlinear multiple regression showed the best potential for predicting E∗.

Multiple regression showed that neither habitat characteristics nor habitat deterioration significantly affected rates of biomass build-up.

Finally, combining above results with weights obtained from multiple regression showed that controlling IEQ by acting on single parameters would require unrealistic set-points.

Multiple regression showed that response allocation was sensitive to the current session immediacy ratio, with greater sensitivity in the long than the short condition.

The model chosen by using multiple regression showed, that plots located in the zone with noise exceedance at night were about 57% cheaper than those located outside this zone.

Multiple regression shows to what extent changes in each independent variable are predictive of changes in the dependent variable (organization).

Again, the multiple regression shows the effect of PLAB Part 2 (β=0.278) is stronger than that for IELTS (β=0.187).

IELTS scores correlated significantly with later performance, multiple regression showing that the effect of PLAB1 (β=0.496) was much stronger than the effect of IELTS (β=0.086).

However a multiple regression shows that the predictive effect of PLAB Part 1 (β=0.496) is very much stronger than the effect of IELTS (β=0.086).

Interestingly, the multiple regression shows that BTS trunk angle and STS ratio parameters (strongly linked with trunk flexion) were significantly linked to the functional abilities of all the subjects of both groups.