2. SamplingA process used in statisticalanalysis in which apredetermined number ofobservations will be takenfrom a larger population
3. The Sampling Design Process Define the Population Determine the Sampling Frame Select Sampling Technique(s) Determine the Sample Size Execute the Sampling Process
4. Key sampling concepts
5. Key ideas
6. Sampling frame
7. Classification of Sampling Techniques Sampling Techniques Nonprobability Probability Sampling Techniques Sampling TechniquesConvenience Judgmental Quota Snowball Sampling Sampling Sampling Sampling Simple Systematic Stratified Cluster Other Sampling Random Sampling Sampling Sampling Techniques Sampling
8. 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 ones class. Generalization to a population can seldom be made with this procedure.. ………..
9. Judgmental SamplingA form of convenience sampling in which the population elements are selected based on thejudgment of the researcher.Test marketsPurchase engineersselected in industrialmarketing researchBellwether precinctsselected in voting behaviorresearch (Exit poll?)
10. Quota sampling For example, anA pre-defined interviewernumber (or quota) may be given the task ofof people who interviewing 25 • On a weekday morning,meet certain women with toddlers in acriteria are town centresurveyed. • Seven of these women should be aged under 30 years, the instructions • Ten should be aged between may specify 30 and 45 years, that • Eight should be aged over 45 years.
11. Snowball SamplingIn snowball sampling, an initialgroup of respondents is selected,usually at random.After being interviewed, theserespondents are asked to identifyothers who belong to the targetpopulation of interest.Subsequent respondents areselected based on the referrals.
12. Probability samples
15. Cluster sampling is appropriate when itis very time consuming or expensive tochoose the individuals one at a time
16. Multistage Sampling
17. Choosing Nonprobability vs. Table 11.4 cont. Probability Sampling Conditions Favoring the Use ofFactors Nonprobability Probability sampling samplingNature of research Exploratory ConclusiveRelative magnitude of sampling Nonsampling Samplingand nonsampling errors errors are errors are larger largerVariability in the population Homogeneous Heterogeneous (low) (high)Statistical considerations Unfavorable FavorableOperational considerations Favorable Unfavorable