The statistical proportion of each SSCB occurring with different confidence intervals is shown in Fig. 10.
Open image in new window Fig. 10 Statistical proportion of the SSCBs.
As the ranges have been collected from real world data by doing statistical proportion operation (e.g. top 30%% values are high) for deciding different level (i.e. high, medium and low), using trapezoidal membership function is logical as it deals with ranges with flat region better.
Performance of five risk adjustment models was evaluated from three aspects: statistical indicators, proportions of true cases identified by models, and characteristics of predicted cases.
Main outcome measure Proportion of protocols and publications that did not provide key information about sample size calculations and statistical methods; proportion of trials with discrepancies between information presented in the protocol and the publication.
Each sample was observed by Olympus fluorescence microscope to be classified to different stages by the developmental characteristics of both the Micronucleus and Macronucleus during conjugation and counted many enough cells to conclude the statistical number proportion.
This statistical test of proportions compares the observed proportions of an event (here, SNPs) in k samples (here, strains), uses a chi-squared test to seek significant differences among the proportions, and subsequently adjusts the confidence intervals for each sample.
Statistical analysis included proportions, correlations and Bland Altman analysis.
Statistical analysis, including proportions, means, and standard deviations (SDs), were compiled for the following variables: demographic and injury information, rehabilitation charges, medical complications, associated injuries, and surgical procedures.
