ABSTRACT
This chapter presents an overview of inferential statistics and hypothesis testing, and describes many statistical techniques, along with examples of their use in analyzing retail data. It provides guidelines to help understand which statistical technique is appropriate given certain circumstances. Inferential statistics takes analysis one step by attempting to draw conclusions about the processes underlying the data. At the heart of inferential statistics is the concept of a sample and a population. A population is considered the universe of all possible outcomes. A sample is just a small representation of the population. Confidence intervals consider the variation in the population and give an estimate for where the true population parameter lies. Confidence intervals and hypothesis testing are closely related. Confidence intervals provide the likely range for values in the population, whereas hypothesis testing tests whether the true value in the population is equal to a value or range of values.
