ABSTRACT
This chapter introduces the main ideas of statistical inference in the context of a simple model. A statistical analysis starts with a model of the population. This model takes the form of a random variable with some distribution depending on some unknown parameter(s). The chapter shows how to provide a confidence interval of estimates for a parameter of interest. Statisticians often use a summary of data that is called the p-value: the probability of obtaining at least the observed sample mean. There are two types of error that can be made by a statistician: Type I and Type II errors. The Type I error is also called a false positive and the Type II error is also known as a false negative. The chapter also provides examples of the two most common types of statistical inference: confidence intervals and hypothesis tests.
