Computational Statistics

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Computational Statistics

01. Start with R + Git

The importance of reproducibility. Ideas of computational statistics, data science, and machine learning. Some resources for starting with R + RStudio + Git + GitHub.

02. Data Viz

Examples, good and bad. Theory underlying what makes a viz good and bad. Tools to implement viz tasks.

03. Wrangling

Data wrangling skills are among the most important to hone.

04. Simulating

Simulating scenarios, simulating datasets, simulating random variables.

05. Permutation Tests

Simulating scenarios, simulating datasets, simulating random variables.

06. Bootstrapping

The sample as a proxy for the unknown population. Sample from said proxy population (i.e., the sample) to generate a sampling distribution. Bootstrap.

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© Jo Hardin, 2025 -- jo.hardin@pomona.edu -- https://hardin47.netlify.app/

Math 154 -- Computational Statistics -- Pomona College