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Comparing percentages from different groups with different sample sizes requires careful consideration of the underlying sample distributions and statistical methods used. One approach is to calculate confidence intervals for the percentages, which provide a range of plausible values accounting for sampling variability. Additionally, techniques such as bootstrapping or resampling methods can be employed to generate simulated datasets and estimate confidence intervals for the percentages, taking into account the variability introduced by differences in sample sizes. When performing hypothesis testing on percentage data, researchers may use chi-square tests or Fisher's exact tests to assess the statistical significance of observed differences between groups, adjusting for sample size discrepancies. Overall, researchers should aim to select appropriate statistical methods that account for differences in sample sizes and provide robust and interpretable comparisons of percentage data across groups