Time series plots in R are totally customizable using the ggplot2 package, and can come out with a look that is clean and sharp. However, you usually end up fighting with formatting the x-axis and other options, and I explain in my blog post.
GPower case example shows a use-case where we needed to select an outcome measure for our study, then do a power calculation for sample size required under different outcome effect size scenarios. My blog post shows what I did, and how I documented/curated the results.
A/B testing seems straightforward, but there are a lot of picky details. What A and B conditions do you actually test? How long do you run the test? How do you calculate the statistics for the test? Answer your questions by taking this LinkedIn Learning course.