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Exact(2)
The results are presented as means±SD for normal distributed data, median and range for remaining data.
Pearson's Chi-square test was used when more than 80% of data had an expected value greater than 5 and Fisher's Exact Test for remaining data with smaller expected values (at least 20% of data having values less than 5).
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The number of remaining data points for each analyte is shown in Table 2.
The previously published descriptors were used for MUSK2, QSAR, BBB and PGP, while for the remaining data sets MACCS keys (166 bit; frequency of substructures) were used as structure descriptors in the following.
QUASI-P, on the other hand, failed for one series (patient 7, stress, basal), but was applied successfully for the remaining data.
For the remaining data sets random partitions were generated.
For the remaining data, the distribution was normal and ANOVA test was used.
For the remaining data, whose distribution was normal, one-way ANOVA followed by complementary Tukey tests was used.
To address this problem, we present a technique called speculative plan execution, an out-of-order method that capitalizes on knowledge gained from prior executions as a means for overcoming remaining data dependencies between plan operators.
This involves removing one point from the data set at random, determining the new corresponding correlation coefficients, a, b, c, and d, for the remaining data, and then comparing the single removed point experimental value to the new correlation value.
Only these three databases were used for the remaining data sets.
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