Chapter 7 Sampling
The third portion of this book introduces statistical inference. This chapter is about sampling. Sampling involves drawing repeated random samples from a population. In Section 7.1, we illustrate sampling by working with samples of white and red balls and the proportion of red balls in these samples. In Section 7.2, we present a theoretical framework and define what is the sampling distribution. We introduce one of the fundamental theoretical results in Statistics: the Central Limit Theorem in Section 7.3. In Section 7.4, we present a second sampling activity, this time working with samples of chocolate-covered almonds and the average weight of these samples. In Section 7.5, we present the sampling distribution in other scenarios. The concepts behind sampling form the basis of inferential methods, in particular confidence intervals and hypothesis tests; methods that are studied in Chapter 8 and Chapter 9.
Needed packages
We now load all the packages needed for this chapter (this assumes you’ve already installed them). The
moderndive and infer packages contain functions and data frames used in this chapter.
library(tidyverse)
library(moderndive)
library(infer)
