Sentence examples for between the error score from inspiring English sources

However, the regression between the error score and self-estimated ancestry proportions shows a positive relationship for Native American ancestry [β = 0.008; r2 = 0.023; p = 0.025], and a negative relationship for European ancestry [β = −0.009; r2 = 0.042; p = 0.002].

Further confirming this finding, linear regression between the error score and self-estimated ancestry proportions shows a positive relationship with Native American ancestry [β = 0.010; r2 = 0.082; p<0.001], and a negative relationship with European ancestry [β = −0.009; r2 = 0.092; p<0.092].

When we repeat the analyses without the photos of the four individuals who have South American family origins, there are no significant relationships between the independent variables and the error score, except for age in the student sample (p = 0.008).

The error score was calculated by integrating the distances between the mouse and platform every 0.5 sec in each trial.

The error scores reflect the number of misplacements.

Table 2 summarizes the error scores of the two groups.

The Rank rows of Table 1 are likely to be of greater practical significance than comparison between the average error scores themselves.

To further examine variation in error score, we use multiple linear regression to examine the relationship between rater error score and the rater's age, self-estimated Native American and European ancestry proportions, education level, and income.

T-tests are used to determine if there is a significant difference between the mean error scores of the observers and the mean error score of the simulated random observers, as well as to determine whether there is a difference between the mean error score of the MVD and student sample.

We found that the PRI and "between errors score in the SWM" for the MPH-off condition were significantly and positively correlated with each other.

Neither spatial working memory strategy score (p = 0.3) nor between search error score (p = 0.2) predicted the presence of reinforcement-related speeding.