3.2 Sampling Design

Sample vs. Population Recall our discussion about sample vs. population. The entire group of individuals that we are interested in is the population. E.g. American males ages 18-22, all students currently attending Ursinus, the current House of Representatives, all people who have worked at Walmart since 1990, etc.

A sample is a subset of the population that we examine in order to gather information. The idea is to choose a sample of the population that represents the population as a whole. This, of course, is the main problem in sample design; that is, the method used to choose the sample from the population. When the population is manageable, there is no need.

One popular method of sampling is to physically send out surveys. Here it is important to include the response rate; that is, the percentage of people who responded. A voluntary response survey consists of people who choose themselves by responding to a general appeal (e.g. flyers, newspaper ad, TV ad, internet, etc) People with particularly strong opinions are most likely to respond, which is a bias of this method.

Online polls are particularly problematic. A conservative blog that regularly features articles and discussions sympathetic to conservative views will tend to have mostly conservative readers. Hence, any polls on the blog will be taken by mostly conservatives and will not be an accurate representation of everyone’s opinion. Online polls can also be “hijacked” in the sense that if liberal blogs find out about the conservative blog’s poll, then they send all their readers over to vote. At first, this may seem to balance things out, but it can end up being a game of “who can recruit the most people. People also have ways to vote more than once (e.g. a college campus with computer labs.)

Simple Random Sample A simple random sample (SRS) is the simplest way to randomly sample (hence the name). In an SRS, the individual all subjects are chosen from among the population at random or “out of a hat.” One can use a random number table or generator for a SRS. SRS is one example of a general class of sampling techniques known as probability sample.

A probability sample is any sample chosen by chance (there are multiple ways to do this). Besides SRS, another example of a probability sample is a stratified random sample. For a stratified random sample, divide the population into groups of similar individuals, called strata. Then choose a separate SRS in each stratum and combine. Stratum usually share some common characteristic e.g. grade, weight class, income level.

Problems with Sampling Certain topics attract certain people Certain topics attract certain people Access Access Bad marketing Bad marketing Question phrasing Question phrasing Embarrassing question Embarrassing question Nonresponse BiasResponse Bias Undercoverage occurs when some groups in the population are left out of choosing the sample.