Why Sample?

Why not everyone?

Sampling

A process used in statistical analysis in which a predetermined number of observations will be taken from a larger population

The Sampling Design Process

Define the Population

Determine the Sampling Frame

Select Sampling Technique(s)

Determine the Sample Size

Execute the Sampling Process

Key sampling concepts

Key ideas

Sampling frame

Classification of Sampling Techniques

Sampling Techniques

Nonprobability

Sampling Techniques

Probability

Sampling Techniques

Convenience

Sampling

Judgmental

Sampling

Quota

Sampling

Snowball

Sampling

Systematic

Sampling

Stratified

Sampling

Cluster

Sampling

Other Sampling

Techniques

Simple

Random

Sampling

Convenience Sampling

Subjects are selected because they are easily accessible.

This is one of the weakest sampling procedures.

An example might be surveying students in one's class.

Generalization to a population can seldom be made with this procedure.. ………..

Judgmental Sampling

Test markets

Purchase engineers selected in industrial marketing research

Bellwether precincts selected in voting behavior research (Exit poll?)

A form of convenience sampling in which the population elements are selected based on the judgment of the researcher.

Quota sampling

A pre-defined number (or quota) of people who meet certain criteria are surveyed.

• On a weekday morning,

For example, an interviewer

may be given the task of

interviewing 25 women with toddlers in a town centre

• Seven of these women should be aged under 30 years,

• Ten should be aged between 30 and 45 years,

• Eight should be aged over 45 years.

the instructions may specify

that

Snowball Sampling

In snowball sampling, an initial group of respondents is selected, usually at random.

After being interviewed, these respondents are asked to identify others who belong to the target population of interest.

Subsequent respondents are selected based on the referrals.

Probability samples

How?

Similarly………..

Cluster sampling is appropriate when it

is very time consuming or expensive to

choose the individuals one at a time

Multistage Sampling

Choosing Nonprobability vs. Probability Sampling

Conditions Favoring the Use of

Factors

Nonprobability sampling

Probability sampling

Nature of research

Exploratory

Conclusive

Relative magnitude of sampling and nonsampling errors

Nonsampling errors are larger

Sampling errors are larger

Variability in the population

Homogeneous (low)

Heterogeneous (high)

Statistical considerations

Unfavorable Favorable

Operational considerations Favorable Unfavorable

Table 11.4 cont.