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Unformatted text preview: Chapter 12 Sample Plan MKTG 3710 Audhesh Paswan Basic Concepts in Samples and Sampling • Population: the entire group under study as defined by research objectives… • Census: an accounting of the complete population Population is defined in specific terms such as “heads of households located in areas served by the company who are responsible for making the pest control decision.” • Sample: a subset of the population that should represent the entire group Basic Concepts in Samples and Sampling… cont. • Sample unit: the basic level of investigation… consumers, store managers, shelffacings, teens, etc. The research objective should define the sample unit • Sampling error: any error that occurs in a survey because a sample is used • Sample frame: a master list of the entire population • Sample frame error: the degree to which the sample frame fails to account for all of the defined units of the population…a telephone book listing does not contain unlisted numbers Reasons for Taking a Sample • Practical considerations such as cost and population size • Inability of researcher to analyze huge amounts of data generated by census • Samples can produce precise results Two Basic Sampling Methods • Probability samples: members of the population have a known chance (probability) of being selected into the sample • Nonprobability samples: instances where the chances (probability) of selecting members from the population into the sample are unknown Two Basic Sampling Methods Probability  Simple Random Sampling • Simple random sampling: the probability of being selected into the sample is “known” and equal for all members of the population • Blind Draw Method • Random Numbers Method • Advantage: • Known and equal chance of selection…therefore it IS a probability sample! • Easy method when there is an electronic database • Disadvantages: (Overcome with electronic database) • Complete accounting of population needed • Cumbersome to provide unique designations to every population member Two Basic Sampling Methods Probability  Systematic Sampling • Systematic sampling: way to select a random sample from a directory or list that is much more efficient than simple random sampling • Skip interval=population list size/sample size • Advantages: • Approximate known and equal chance of selection..it is a probability sample plan • Efficiency..do not need to designate every population member • Less expensive…faster than SRS • Disadvantage: • Small loss in sampling precision Two Basic Sampling Methods Probability  Cluster Sampling • Cluster sampling: method in which the population is divided into groups (clusters), any of which can be considered a representative sample • Area sampling • Advantage: • Economic efficiency…faster and less expensive than SRS • Disadvantage: • Cluster specification error…the more homogeneous the clusters, the more precise the sample results A twostep area cluster sample (sampling several clusters) is...
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 Spring '08
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