If we were able to gather data on every member of our population, say the average (we will define "average" more carefully in a subsequent section) amount of money spent on textbooks by each first-year student at your college during the 2009-2010 academic year, the resulting number would be called a parameter. We seldom see parameters, however, since surveying an entire population is usually very time-consuming and expensive, unless the population is very small or we already have the data collected. You are probably familiar with two common censuses: the official government Census that attempts to count the population of the U.S. every ten years, and voting, which asks the opinion of all eligible voters in a district. The first of these demonstrates one additional problem with a census: the difficulty in finding and getting participation from everyone in a large population, which can bias, or skew, the results. There are occasionally times when a census is appropriate, usually when the population is fairly small. For example, if the manager of Starbucks wanted to know the average number of hours her employees worked last week, she should be able to pull up payroll records or ask each employee directly. Since surveying an entire population is often impractical, we usually select a sample to study. We will discuss sampling methods in greater detail in a later section.  For now, let us assume that samples are chosen in an appropriate manner.  If we survey a sample, say 100 first-year students at your college, and find the average amount of money spent by these students on textbooks, the resulting number is called a statistic.

Sometimes, determining whether or not data is categorical or quantitative can be a bit trickier.  In the next example, teh data collected is in numerical form, but it is not quantitative data.  Read on to find out why.   The examples in this page are discussed further in the following video: https://youtu.be/mxZqyB01qPY