We then tied these sampling exercises to terminology and mathematical notation related to sampling in Subsection 7.3.1. Our study population was the large bowl with \(N\) = 2400 balls, while the population parameter, the unknown quantity of interest, was the population proportion \(p\) of the bowl’s balls that were red. Since performing a census would be expensive in terms of time and energy, we instead extracted a sample of size \(n\) = 50. The point estimate, also known as a sample statistic, used to estimate \(p\) was the sample proportion \(\widehat{p}\) of these 50 sampled balls that were red. Furthermore, since the sample was obtained at random, it can be considered as unbiased and representative of the population. Thus any results based on the sample could be generalized to the population. Therefore, the proportion of the shovel’s balls that were red was a “good guess” of the proportion of the bowl’s balls that are red. In other words, we used the sample to infer about the population.