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.