Analysis of prevalence of malaria parasites
To determine whether the prevalence of each Plasmodium species is geographically biased, Fisher exact test was performed on software R (version 3.2.4) on the distribution table. The null hypothesis under the Fisher exact test is, “prevalence and region are independent, i.e., prevalence of malaria parasite does not change as geographic location changes”. For the test, 107 random tables with the same column and row totals as the observed data, assuming row and column independence, were generated. The P value cited is the sum of the probabilities of all generated tables that have individual probabilities smaller than those in the observed table. To compare each observed value with its expected value under null hypothesis, Chi square tests were performed in R on the observed table to generate each expected value under the null hypothesis.
Analysis of prevalence of malaria parasitesTo determine whether the prevalence of each Plasmodium species is geographically biased, Fisher exact test was performed on software R (version 3.2.4) on the distribution table. The null hypothesis under the Fisher exact test is, “prevalence and region are independent, i.e., prevalence of malaria parasite does not change as geographic location changes”. For the test, 107 random tables with the same column and row totals as the observed data, assuming row and column independence, were generated. The P value cited is the sum of the probabilities of all generated tables that have individual probabilities smaller than those in the observed table. To compare each observed value with its expected value under null hypothesis, Chi square tests were performed in R on the observed table to generate each expected value under the null hypothesis.
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