2-1

Sample Sample DesignDesign

SampleSubset of a larger population

PopulationAny complete group

PeopleSales peopleStoresStudentsTeachers

CensusInvestigation of all individual elements that

make up a population

Sampling FrameA list of elements from which the sample may

be drawn

Such asMailing lists Commercial directoriesTelephone directoryDatabases

Categories of Sampling

Probability samplingKnown chances Every member gets a chance

Nonprobability samplingUnknown Probability of selecting any

particular member

Nonprobability SamplingConvenienceJudgmentQuotaSnowball

Convenience Sampling Obtaining the people who are most

conveniently (readily) available

Judgment (purposive) Sampling An experienced individual selects the sample

based on his/her judgment about some characteristics required of the sample member

Quota Sampling Various subgroups in a population are

represented on relevant sample characteristics according to researchers desire

Snowball Sampling Initial members are selectedAdditional members are selected based on

information provided by the initial participants

1

1

2 3

Probability SamplingSimple random sampleSystematic sampleStratified sampleCluster sampleMultistage area sample

Simple Random Sampling Every member of the population has an equal

chance of being selected in the sample.

Simple random sampling

Systematic Sampling A simple processEvery nth name from the list will be drawn

Systematic sampling

Stratified SamplingSubsamples are drawn within different strataEach stratum is more or less equal on some

characteristic

What is the right stratified sample?

Cluster SamplingDividing the population into groups, or

clusters,Selecting some of these clusters at

random. Obtaining the sample by choosing all the

members within each of the selected clusters.

Section 4

Section 5

Section 3

Section 2Section 1

Population Element Possible Clusters

Airline travelers Airports travelers Planes travelers

Sports fans Football fans Basketball fans Car race fans

Karate fans