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For the three conditions tested, the data for the ΔclrA strain were similar to the WT strain.
Varying the number of communities formed by using the infomap community detection algorithm tested the data; for each set of communities, also varied was the α value, used to compute the Katz centrality values of each node over the entire graph.
Kolmogorov-Smirnov and Levene'test first tested the data for normality and homoscedasticity respectively.
We tested the data for normality with Levene's test.
However, we tested the data for such a cohort effect in two ways.
We tested the data for assumptions of normality and equality of variances before conducting parametric tests (SPSS version 15.0).
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The Shapiro-Wilk's test was used to test the data for normality.
To test the data for normality of distribution, the Shapiro-Wilk test was used.
The purpose of meta-analysis is not just to obtain a summary estimate of treatment effect, but also to test the data for consistency (heterogeneity testing).
The purpose is to test the data collection for face and content validity.
In all experiments, we used chi-square tests to analyze the data for a preferential choice.
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CEO of Professional Science Editing for Scientists @ prosciediting.com