This is a step-by-step tutorial on how to create a diverging bar chart starting from scratch - from data preparation to final visualization.

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This project demonstrates how small sample sizes in A/B testing can lead to inconclusive results and how adjusting sample sizes through power analysis reveals statistically significant effects. Simulated data is used to compare p-values, conversion rates, and statistical power before and after sample size adjustment. Visualizations include ggstatsplot, ggpubr, ggsignif, and ggpmisc.