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Testing the data for normality showed a non-normal distribution of the CRP data, with a positive skewness and a significant difference from a normal distribution seen by Kolmogorov Smirnov test [D 84) = 0.258, p < 0.001].
After testing the data for normal distribution and equal variance, differences between two groups were analyzed by the unpaired Student's t-test, and differences between multiple groups were analyzed by ANOVA.
Differences in mean RTOP scores for PDs who taught an entire course and those who taught part of a course were analyzed using a t-test after testing the data for normality.
Logistic regression analyses were conducted using SPSS version 18.0 to estimate the strength of association between exposure to interventions and needle sharing, condom usage and HIV testing; the data for this analysis are grouped at the state (rather than district) level.
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The Shapiro-Wilk's test was used to test the data for normality.
For the three conditions tested, the data for the ΔclrA strain were similar to the WT strain.
Kolmogorov-Smirnov and Levene'test first tested the data for normality and homoscedasticity respectively.
We tested the data for normality with Levene's test.
To test the data for normality of distribution, the Shapiro-Wilk test was used.
However, we tested the data for such a cohort effect in two ways.
Non-parametric statistics tested the data for differences in their ability to perform the tests across 25(OH D categories.
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