Summary
In biostatistics, one of the most common ways of performing statistical tests is to use specific hypothesis test methods.
In this chapter, we learned what are the most important libraries for biostatistics hypothesis tests in Python and how to use them.
Additionally, we learned about libraries for predictive biostatistics in Python and how to write code for implementing linear regression methods.
Further, we learned how to interpret hypothesis tests and effect sizes. We learned how to differentiate statistical significance from the actual magnitude of the effect.
Finally, we learned how to choose which method to use to answer different scientific or research questions.
In the next chapter, we will learn more about predictive biostatistics, specific studies in which it is used, how to set up a research problem, and how to perform analysis practically using Python.
