Skip to main content

Chapter 5 Foundations for inference

Statistical inference is primarily concerned with understanding and quantifying the uncertainty of parameter estimates. While the equations and details change depending on the setting, the foundations for inference are the same throughout all of statistics. We start with a familiar topic: the idea of using a sample proportion to estimate a population proportion. Next, we create what's called a confidence interval , which is a range of values where the true population value is likely to lie. Finally, we introduce a hypothesis testing framework, which allows us use data to formally evaluate claims about the population, such as whether a survey provides strong evidence that a candidate has the support of a majority of the voting population.