Activity: Practice It (Bootstrapping!)

1. Estimated Time: 15 minutes · Your Task
2. Bootstrapping is the computational process of iteratively computing the same statistic from samples that differ just slightly due to random sampling with replacement.
3. Bootstrapping returns ~1000 statistics, each just slightly different due to chance, that approximate the true shape of the sampling distribution for that statistic.
4. In this activity, you will practice bootstrapping using the workshops/onsen.csv dataset.
5. Please complete the following steps: Load in your dataset. Select a variable of interest. Select a statistic of interest and compute it one time (eg. xbbar, sbar, rbar, sigma_s, etc.).
6. Bootstrap your dataset to get 1000 slightly different copies of the dataset.
7. Using grouping by a unique id for each bootstrapped copy of the dataset, calculate the statistic again.
8. Estimate the mean and standard error of the bootstrapped statistics. (The standard deviation of a sampling distribution is the standard error.)
9. Explain the result in 1-2 sentences.
10. Submission Requirement: Copy and paste your commented code into the CANVAS submit textbox below. Copy your mean and standard error for the statistic, and your description.

Remember to submit on CANVAS (1 pt) — graded on completion. (Individual)