COMM 211

• purposive sampling
• snowball sampling
• using available subjects
• quota sampling
• selecting informants

• Selecting particular kinds of people. Talking to a certain number from ear category.
• Ex. 30 people that live in dry county and 30 people that live in wet county

• finding someone who can tell you about a group of people.
• Ex. a member of a book group can tell you about the whole book.

Finding one person, having them introduce you to others like themselves.

Seeking out a particular kind of person. Talking to the ones you think will be most useful.

a method for drawing a sample from a population in two or more stages. Typically done when you can't list the members of a sample but you can list groups of clusters

A procedure in stratified sampling in which the researcher selects a disproportionately large number of subjects from a particular group (stratum)

The number of participants that we recruit from each subgroup is equal to their proportion in the population.

if members of the population have been sampled disproportionately, before researchers can make a representation of the population, they have to weight the responses.

Random samples are drawn from within particular categories of the population

Type 1 error

type 2 error

• Random Chance
• There is an inverse relationship
• Research is biased
• Measurement is bad
• Sampling problems
• Other design issues

Selecting a group of subjects from a sampling frame so that each individual is chosen entirely by chance.

A sample obtained by taking every “nth” subject after a random start. “n” is calculated by knowing how many subjects you want in your sample.

Random samples are drawn from within particular categories (or “strata”) of the population.

Your hypothesis is proven true. But it is proven false in the real world.

Your hypothesis is proven false, but it is true in the real world.