A medical research center is testing a new weight loss treatment. They advertise on a social media site that they are looking for volunteers to participate. There is sampling bias because the sample will be limited to people who use the social media site where they advertised. The individuals who choose to participate may be different from the overall population. For example, volunteers may be individuals who are already actively trying to lose weight. This is not a representative sample because the sample may have characteristics that are different from the population of interest.

The marketing department for a large retail chain wants to survey their customers about a new advertising plan. They go into one of their largest New York City stores on a Tuesday morning and survey the first 50 people who make a purchase. There is sampling bias for a number of reasons. They are only sampling at one store, in New York City; there may be differences between the customers at this store and those that shop at their other locations. By conducting their survey on a Tuesday morning they are limiting themselves to individuals who are out shopping at that time; the sample may lack people who work during the day. Finally, they only survey people who make a purchase; individuals who do not make a purchase, perhaps because they are not satisfied with the store, will not be included in their sample. This is not a representative sample because the sample selected may be different from the population of interest.

An institutional researcher is conducting a study of World Campus students’ attitudes toward community service. He takes a list of all 12,242 World Campus students and uses a random number generator to select 30 students whom he contacts to complete the survey. This researcher used simple random sampling because participants were selected from the overall population in a way that each individual had an equal chance of being selected.

A student wants to learn more about the languages spoken in her town. She has access to the census forms submitted by all 3,500 households in her town. It would take too long for her to go through all 3,500 forms, so she uses a random number generator to select 100 households. She finds those 100 census forms and records data concerning the languages spoken in those households. This is a simple random sample because the sample of 100 households was selected in a way that each of the 3,500 households had an equal chance of being selected.

A weight loss company wants to compare how much weight adults lose on their supplement versus a competitor's supplement. To recruit participants, they post an advertisement in a newspaper asking for adults who want to lose weight. This is an example of a volunteer sample which is a convenience sampling method. The researchers are using a sample of individuals who volunteer to participate.

A chocolate company wants to know if customers prefer their dark chocolate with or without peanuts. They set up a table in a grocery store on a Monday morning, offer customers samples of their dark chocolate with and without peanuts, and ask which they prefer. This is an example of a convenience sampling method. The sample is not being selected using any probability-based method and may not be representative of the company's intended population. People who grocery shop may be a special subset of the population.  For example, people who do not work traditional full-time jobs may be more likely to grocery shop at that time. The researchers are using a sample of individuals who happen to be grocery shopping on a Monday morning and who volunteer to eat their chocolate.