Sample Size and Sampling Mechanics Sampling
CHAPTER 12
SAMPLING MECHANICS
Sampling is an activity that involves the selection of individual people, data or things, from a target population/universe.
A population, or universe, is the entire set people data or things that is the subject of exploration.
A census involves obtaining information, not from a sample, but rather from the entire population or universe.
A sample (as opposed sampling) is a subset of the population/universe.
For Marketing Research purposes, sampling usually involves people, not data or things.
Sampling Plans are strategies and mechanics for selecting members of the sample from the population:
1. Define the population. It is usually limited based on some set of characteristics, e.g., males, aged 21-39, who have consumed alcoholic beverages within the past 3 months for a beer study. 2. Choose data collection methodology. What kind of information do you require from the sample, how will they be identified, where are they available, etc. 3. Set sampling frame. This is as exhaustive a list as operationally and economically possible that represents the population and is also accessible utilizing the selected methodology. 4. Choose sampling method. • Probability samples are those that allow all members of the sampling frame an equal opportunity of selection. Probability samples include Simple Random, Systematic, Stratified and Cluster sampling • Nonprobability samples do not allow all members of the sampling frame an equal opportunity of selection. Nonprobability samples include Convenience, Judgment, Quota and Snowball sampling. 5. Determine sample size (subject of Chapter 13) 6. Develop operational procedures for extracting sample from the population (logic and controls) 7. Executed the operational plan
Sampling error. Random sampling error always exists.
Administrative errors are generally controllable when properly identified and monitored. Results from two samples,
SAMPLING MECHANICS
Sampling is an activity that involves the selection of individual people, data or things, from a target population/universe.
A population, or universe, is the entire set people data or things that is the subject of exploration.
A census involves obtaining information, not from a sample, but rather from the entire population or universe.
A sample (as opposed sampling) is a subset of the population/universe.
For Marketing Research purposes, sampling usually involves people, not data or things.
Sampling Plans are strategies and mechanics for selecting members of the sample from the population:
1. Define the population. It is usually limited based on some set of characteristics, e.g., males, aged 21-39, who have consumed alcoholic beverages within the past 3 months for a beer study. 2. Choose data collection methodology. What kind of information do you require from the sample, how will they be identified, where are they available, etc. 3. Set sampling frame. This is as exhaustive a list as operationally and economically possible that represents the population and is also accessible utilizing the selected methodology. 4. Choose sampling method. • Probability samples are those that allow all members of the sampling frame an equal opportunity of selection. Probability samples include Simple Random, Systematic, Stratified and Cluster sampling • Nonprobability samples do not allow all members of the sampling frame an equal opportunity of selection. Nonprobability samples include Convenience, Judgment, Quota and Snowball sampling. 5. Determine sample size (subject of Chapter 13) 6. Develop operational procedures for extracting sample from the population (logic and controls) 7. Executed the operational plan
Sampling error. Random sampling error always exists.
Administrative errors are generally controllable when properly identified and monitored. Results from two samples,