This chapter shifts from probability models to sampling distributions — the distributions of statistics computed from repeated samples. Students examine how sample proportions and sample means vary from sample to sample, and they learn the Central Limit Theorem, which explains how many sample means form an approximately normal distribution. Understanding sampling distributions is essential for later inference about populations.