Mkt 232 Chapter 12

Front 1

basic level of investigation

Back 1

sample unit

Front 2

subset of the population that should represent the entire group

Back 2

sample

Front 3

entire group under study as defined by research objectives

Back 3

population

Front 4

accounting of the complete population

Back 4

census

Front 5

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

Back 5

sampling error

Front 6

ones in which members of the population have a known chance (probability) of being selected into the sample

Back 6

probability sampling

Front 7

instances in which the chances (probability) of selecting members from the population into the sample are known

Back 7

non-probability samples

Front 8

probability of being selected into the sample is "known" and equal for all members of the population
- blind draw method
- random numbers method

Advantages:
- known and equal chance of selection
Disadvantages:
- complete accounting of population needed
- cumbersome to provide unique designations to ever population

Back 8

simple random sampling

Front 9

way to select a random sample from a directory or list that is much more efficient that 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

Back 9

systematic sampling

Front 10

method in which the population is divided into groups, any of which can be considered a representative sample.
- area sampling - geographic area is divided into clusters

advantages:
- economic efficiency - faster and less expensive than simple random sampling

disadvantages:
- cluster specification error - the more homogeneous the clusters, the more precise the sample results

Back 10

cluster sampling

Front 11

separates the population into different subgroups (strata) and samples all subgroups

advantages:
- more accurate overall sample of skewed population

disadvantages:
- more complex sampling plan requiring different sample size for each stratum

Back 11

stratified sampling

Front 12

some members of the population have no chance of being selected - not based on fairness, equity, or equal chance

Back 12

nonprobability sampling

Front 13

researcher or interviewer uses a high-traffic location such as a busy pedestrian area or a shipping mall as a sample frame of which to intercept potential respondents
- error occurs in the form of members of the population who are infrequent or nonusers of that location

Back 13

convenience samples

Front 14

researcher uses his or her judgment or that of some other knowledgeable person to identify who will be in the sample.
- subjectivity enters here, and certain members will have a small chance of selection than others

Back 14

judgment samples

Front 15

respondents are asked for their names or identities of others like themselves who might quality to take part in the survey
- members of the population who are less known, disliked, or whose opinions conflict with the respondent have a low probability to being selected

Back 15

referral samples

Front 16

researcher identifies quota characteristics such as demographic or product use factors and uses these to set up quotas for each class of respondent.
- often used to ensure that convenience samples will have desired proportion of different respondent classes

Back 16

quota samples

Front 17

1. define the population
2. obtain a "listing" of the population
3. design the sample plan (size, method)
4. draw the sample
5. validate the sample
6. resample, if necessary

Back 17

steps in the sampling process