> For the complete documentation index, see [llms.txt](https://book.thedatascienceinterviewproject.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://book.thedatascienceinterviewproject.com/statistics.md). # STATISTICS - [Probability Basics](https://book.thedatascienceinterviewproject.com/statistics/probability-basics.md): Probability theory is the mathematical foundation of statistical inference, which is indispensable for analyzing data affected by chance, and thus essential for data scientists. - [Probability Distribution](https://book.thedatascienceinterviewproject.com/statistics/probability-distribution.md): Knowing the distribution of data helps us better model the world around us. It helps us to determine the likeliness of various outcomes or make an estimate of the variability of an occurrence. - [Central Limit Theorem](https://book.thedatascienceinterviewproject.com/statistics/central-limit-theorem.md): The theorem gives us the ability to quantify the likelihood that our sample will deviate from the population without having to take any new sample to compare it with. - [Bayesian vs Frequentist Reasoning](https://book.thedatascienceinterviewproject.com/statistics/bayesian-vs-frequentist-reasoning.md) - [Hypothesis Testing](https://book.thedatascienceinterviewproject.com/statistics/hypothesis-testing.md): Hypothesis testing is the process used to evaluate the strength of evidence from the sample and provides a framework for making determinations related to the population - [A/B test](https://book.thedatascienceinterviewproject.com/statistics/a-b-test.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://book.thedatascienceinterviewproject.com/statistics.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.