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After ensuring that there were no significant differences in company or participant characteristics between the groups, we compared respondents' capabilities across the seven 'tudes.
To assess the predictive power of the GE changes between the groups, we employed machine-learning procedures to construct classifiers to predict group membership based on pre- versus post-intervention GE (vacation effect) and regular versus non-regular post-intervention GE data (meditation effect).
To compare variables between the groups we used a Chi2 test.
Today, after gaining more "mileage" with this divisional structure and improving the collaboration between the groups, we are continuing to explore further steps in creating more autonomy.
Finally, despite statistically similar ISSs between the groups, we did not analyze associated injuries which could have revealed a difference between the two cohorts to help explain the results.
To examine the potential confounding effect of concomitant ethanol consumption on elicited manic-like behaviors or the possibility that differences in behaviors could have resulted from differential ethanol intake between the groups, we compared manic-like behaviors between two LHK groups, water only and ethanol (20% v/v versus water) drinking groups (n = 8 each).
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However, since the time required for processing the specimen material was approximately the same between all the groups, we consider that this would not have greatly affected the data between the groups.
To determine the between-time differences within the groups, we used the non-parametric Wilcoxon signed-ranks test.
For the comparison between the two groups we used the Fisher test, considered significant with P <0.05.
Before we look closely at the relationship between the two groups, we need to recognize that the nature of the marketing function varies significantly from company to company.
Although we do not expect differences in the number of agreements between the two groups, we expect the quality of agreements to differ significantly.
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