Determining the Sample Plan

Marketing research
Chapter 11 – Determining the sample plan – step 8

Basic Concepts in Samples and Sampling
Population: the entire group under study as defined by research objectives…
Researchers define populations in specific terms such as “heads of households located in areas served by the company who are responsible for making the pest control decision.”
Example for Terminix Pest Control
“everybody who might use our services”
“heads of households in those metropolitan areas served by Terminix who are responsible for inspect pest control”

Sampling error: any error that occurs in a survey because a sample is used

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: ones in which members of the population have a known chance (probability) of being selected into the sample
Non-probability samples: instances in which 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

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
Disadvantage:
Small loss in sampling precision

Systematic Sampling

Systematic Sampling

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

In one-step cluster sample approach the researcher may believe that the various clusters are sufficiently identical to permit him to concentrate his or her attention on just one area and then generalize the results to the full population.
A two-step cluster sample approach. For the first step the researcher could select a random sample of clusters, and then for the second step, he or she could decide on a probability method to sample individuals within the chosen clusters.
A two-step area cluster sample (sampling several clusters) is preferable to a one-step (selecting only one cluster) sample unless the clusters are homogeneous
Cluster Sampling

Stratified Sampling: When the researcher knows that answers to the research question are likely to vary by subgroups….
Research question: “To what extent do you value your college degree?” Answers are on a 5-point scale: 1=“Not valued at all” and 5=“Very highly valued.”
We would expect the answers to vary depending on classification. Freshman are likely to value less than seniors. We would expect the mean scores to be higher as classification goes up.
We would also expect there to be more agreement (less variance) as classification goes up. That is, seniors should pretty much agree that there is value. Freshman will have less agreement. See next slide…

Two Basic Sampling Methods
Probability
Stratified Sampling
Stratified sampling: method in which the population is separated into different strata and a sample is taken from each stratum
Advantage:
More accurate overall sample of skewed population
Disadvantage:
More complex sampling plan requiring different sample sizes for each stratum

Two Basic Sampling Methods
Nonprobability
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
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

Two Basic Sampling Methods
Nonprobability…cont.
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.
Quota samples: samples that use a specific quota of certain types of individuals to be interviewed

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
Online panel sampling: refers to consumer or other respondent panels that are set up by marketing research companies for the explicit purpose of conducting online surveys with representative samples

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

Developing a Sample Plan
6 steps
Step 1: Define the relevant population (target population is identified by the marketing research study objectives).
Step 2: Obtain a listing of the population.
Step 3: Design the sample method (size and method).