MARKETING MARKETING RESEARCHRESEARCH
Week 3Week 3Session ASession A
IBMS Term 2, 2008-09IBMS Term 2, 2008-09
Today:
•2 x Lectures
•2 x Project Sessions• Project Brief Due – Fri 13th Mar
• Questionnaire Due – Fri 20th Mar
• Coaching Sessions Throughout the Week (W.Moes)
This Week
Today:
•Lecture: Sample Selection (Ch 12)
Break
•Lecture: Sample Selection (Ch 12)
•Class Activity: Review Questions & Case
Determining How to Select a Sample
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Basic Concepts in Sampling
• Population: the entire group under study as defined by research objectives
• Census: an accounting of the complete population (a list)
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Basic Concepts in Sampling
• Sample: a subset of the population that should represent the entire group
• Sample unit: the basic level of investigation
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Basic Concepts in Sampling
• Sampling error: any error in a survey that occurs because a sampling is used– Selection problems– Incorrect sample size
• A sample frame: a master list of the entire population– Telephone List– Customer List– Email List with email addresses
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Basic Concepts in Sampling
• Sample frame error: the sample frame fails to account for all of the population– a telephone book listing does not
contain unlisted numbers– A list of visitors to the EPBS Career
Beurs Stand does not include people that could not make it to the Beurs.
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REMEMBER!
• Two types of errors in sampling:– Sampling error– Sample frame error
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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
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Two Basic Sampling Methods
• Probability samples: members of the population have a known chance (probability) of being selected into the sample
• Non-probability samples: probability of selecting members from the population into the sample are unknown
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Probability Sampling Methods
(probability is known)
• Simple random sampling
• Systematic sampling
• Cluster sampling
• Stratified sampling
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Probability Sampling Methods
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Probability Sampling:Simple Random Sampling
• Simple random sampling: the probability of being selected into the sample is “known” and equal for all members of the population
– E.g., Blind Draw Method
– Random Numbers Method
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Probability Sampling:Simple Random Sampling
– Advantage: • Known and equal chance of selection
– Disadvantages:• Complete accounting of population
needed• Cumbersome to provide unique
designations to every population member
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Probability SamplingSystematic 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
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Probability SamplingSystematic Sampling
– 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
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Probability SamplingCluster Sampling
• Cluster sampling: method in which the population is divided into groups, any of which can be considered a representative sample– Area sampling
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Probability SamplingCluster 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
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Stratified Sampling
• When the researcher knows the answers to the research question are likely to vary by subgroups…
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Stratified Sampling
– Research Question:
“To what extent do you value your college degree?”
Answers are on a five point scale: 1= “Not valued” and 5= “Highly valued”
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Stratified Sampling
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Probability SamplingStratified Sampling
• Stratified sampling: method in which the population is separated into different strata and a sample is taken from each stratum
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Probability SamplingStratified Sampling
– Advantage: • More accurate overall sample of
skewed population…see next slide for WHY
– Disadvantage:• More complex sampling plan
requiring different sample size for each stratum
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Break
• 15 minutes
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Nonprobability Sampling
• With nonprobability sampling methods selection is not based on fairness, equity, or equal chance.
– Convenience sampling
– Judgment sampling
– Referral sampling
– Quota sampling
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Nonprobability Sampling
• May not be representative but they are still used very often. Why?
– Decision makers want fast, relatively inexpensive answers… nonprobability samples are faster and less costly than probability samples.
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Nonprobability Sampling
• May not be representative but they are still used very often. Why?
– Decision makers can make a decision based upon what 100 or 200 or 300 people say…they don’t feel they need a probability sample.
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Nonprobability Sampling
• Convenience samples: samples drawn at the convenience of the interviewer
– Error occurs in the form of members of the population who are infrequent or nonusers of that location
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Nonprobability Sampling
• Judgment samples: samples that require a judgment or an “educated guess” as to who should represent the population
– Subjectivity enters in here, and certain members will have a smaller chance of selection than others
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Nonprobability Sampling
• Referral samples (snowball samples): samples which require respondents to provide the names of additional respondents
– Members of the population who are less known, disliked, or whose opinions conflict with the respondent have a low probability of being selected
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Nonprobability Sampling
• Quota samples: samples that use a specific quota of certain types of individuals to be interviewed
– Often used to ensure that convenience samples will have desired proportion of different respondent classes
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Online Sampling Techniques
• Random online intercept sampling: relies on a random selection of Web site visitors
• Invitation online sampling: is when potential respondents are alerted that they may fill out a questionnaire that is hosted at a specific Web site
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Online Sampling Techniques
• Online panel sampling: refers to consumer or other respondent panels that are set up by marketing research companies for the explicit purpose of conducting surveys with representative samples
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Developing a Sample Plan
• Sample plan: definite sequence of steps that the researcher goes through in order to draw and ultimately arrive at the final sample
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Developing a Sample Plan
1. Define the relevant population.
2. Obtain a listing of the population.
– The incidence rate is the percentage of people on a list who qualify as members of the population
3. Design the sample plan (size and method).
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Developing a Sample Plan
4. Draw the sample.– Substitution methods:
• Drop-down substitution • Oversampling • Resampling
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Developing a Sample Plan
5. Validate the sample.
– Sample validation is a process in which the researcher inspects some characteristic(s) of the sample to judge how well it represents the population.
6. Resample, if necessary.
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Class Activity
• In your groups, draft up a sample plan for
your Research Project. Submit to the
teacher and then you are finished for this
teaching session.
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