1. Sampling Designs and Sampling Procedures
Research Methods in Management
Sampling Designs and Sampling Procedures
Sampling design &
Sampling procedures

2. Sampling Terminology Population (universe) Census Sample
Any complete group of entities that share some common set of characteristics.
Census
An investigation of all the individual elements that make up a population.
Sample
A subset, or some part, of a larger population.

3. Sample Sample is regarded as a representative of the population
Therefore, they must have the characteristics that accurately reflects the population.

4. Why Sample? Pragmatic Reasons Destruction of Test Units
Budget and time constraints.
Limited access to total population.
Destruction of Test Units
Sampling reduces the costs of research in finite populations.

5. Sampling methods Probability Sampling Nonprobability Sampling
A sampling technique in which every member of the population has a known, nonzero probability of selection.
Nonprobability Sampling
A sampling technique in which units of the sample are selected on the basis of personal judgment or convenience.
The probability of any particular member of the population being chosen is unknown.

6. Sampling process
Total
population
Sampling
frame
Sampling
unit

7. Target Population Defining the Target Population Example
What is the relevant population?
Whom do we want to talk to?
Population is operationally defined by specific and explicit tangible characteristics.
Example
Research topic: The effect of brand perception on consumer’s purchase intention of cosmetics.
Target Population: People who regularly use cosmetics.
A population can be the population of the whole country (e.g., Thailand) or the population of some specific area (e.g, Bangkok).

8. Sampling Frame The Sampling Frame (working population)
A group of people or entities that are drawn from the entire population.
The sampling frame may be a group of people or entities whom we can gain access to them. E.g., list, contact directory

9. Consumers whose emails are listed in the customer database/directory
All
consumers
Consumers whose s are listed in the customer database/directory

10. Sampling Units/Planned sample
Sampling Unit/Planned sample
A single element or group of elements subject to selection in the sample.
Computer programs can provide a random selection of sampling units.

11. Consumers whose emails are listed in the database/directory
who are
randomly
selected
Consumers
who actually
answer
the survey
All
consumers

12. Number of Participants
Response rate
A response rate is the result of dividing the number of people who were interviewed by the total number of people in the sample who were eligible to participate and should have been interviewed.
Number of Completed
Surveys
Response rate =
X 100
Number of Participants
Contacted

13. Sampling process in SMEs research
All SMEs in Thailand
(2.7 million firms)
Entire population
SMEs listed in the Thailand's exporters directory
(more than 10,000 firms)
Sampling frame
Planned sample
1,000 companies were randomly selected from the Thailand's exporters directory. Then, the questionnaire were sent to them.
Actual sample
After the questionnaire were sent, 129 out of 1,000 companies returned the survey
(12.9% response rate)

14. Probability Sampling Simple Random Sampling
Assures each element in the population of an equal chance of being included in the sample.

15. Probability Sampling Systematic Sampling Example:
A starting point is selected by a random process and then every n th number on the list is selected.
Example:
All students who have the ID number ends with 1 (e.g., 001, 011, 021, 031, 041) will be selected as the sample.

16. Probability Sampling Stratified Sampling
Simple random subsamples that are more or less equal on some characteristic are drawn from within each stratum of the population.
Proportional Stratified Sample
The number of sampling units drawn from each stratum is in proportion to the population size of that stratum.
Disproportional Stratified Sample
The sample size for each stratum is allocated according to analytical considerations.

17. Percentage in population
Proportional versus Disproportional Sampling example: Mobile phone users
Assume that:
Samples needed = 1,000
Percentage in population
40%
50%
10%
40% % %
(400) (500) (100)
Proportional sample
35% % %
(350) (350) (300)
Disproportional sample

18. Cluster Sampling Cluster Sampling
An economically efficient sampling technique in which the primary sampling unit is not the individual element in the population but a large cluster of elements.
Clusters are selected randomly.
Then every single entity within each cluster is selected as the sample

19. Cluster Sampling Population: Police officers in Bangkok
Clusters (districts) are randomly picked
- Bang-rak - Silom
- Sathon Dindang
- Bangkapi Samsen
- Phayathai Pathumwan
Then, “every police officer within the districts” is recruited as the sample

20. Multistage Area Sampling
Involves using a combination of two or more probability sampling techniques.
Typically, geographic areas are randomly selected in progressively smaller (lower-population) units.
Researchers may take as many steps as necessary to achieve a representative sample.
Progressively smaller geographic areas are chosen until a single housing unit is selected for interviewing.

21. Multistage Area Sampling
District 1
District 2
District 3
City 1
City 2
North
East
Northeast
South
Region level
(biggest scope)
City level
(Randomly selected)
District level
(Randomly selected)

22. Nonprobability Sampling
Convenience Sampling
Obtaining those people or units that are most conveniently available.
For example: interview people in the street who look most helpful.
Judgment (Purposive) Sampling
An experienced individual selects the sample based on personal judgment about some appropriate characteristic of the sample member.
(e.g. Females age between 45 and 60).

23. Nonprobability Sampling
Quota Sampling
Ensures that various subgroups of a population will be represented on pertinent characteristics to the exact extent that the investigator desires.
(e.g. 200 females and 300 males between the age of 45 and 60).

24. Nonprobability Sampling (cont’d)
Snowball Sampling
A sampling procedure in which initial respondents are selected by probability methods and additional respondents are obtained from information provided by the initial respondents.

25. Nonprobability Sampling (cont’d)
Advantages
Speed of data collection
Lower costs
Convenience
Disadvantages
Lack of random selection causes sampling bias.
Sample may not be the accurate representative of the population.

26. What is an appropriate sample size?
Online sample size calculator

27. Bias in sampling Random Sampling Error
The difference between the sample result and the result of a census conducted using identical procedures.
A statistical fluctuation that occurs because of chance variations in the elements selected for a sample.

28. Nonprobability Sampling (cont’d)
Total population: the majority seem to disagree Y N Y N N N Y Y N N N Y N N N N N Y N N N Y N Y Y N N N N N N N N Y Y N N N N Y N N Y N N Y Y N N Y
Agree
Disagree N N N N N N N N N Y N N Y Y N N N N N Y N N N Y N N N Y N Y Y N N N N N Y N N Y N N N N Y N Y N N N N Y N N Y N Y N N N Y N Y Y N N Y N N N Y N N Y N N N Y N Y Y N N N N N N N Y N Y Y Y N N Y N N N N N N N N N N N N Y N N N N N Y N Y Y N N N N Y Y N N N N N N N N N N N Y Y N N N N N N N Y N N N Y Y N N N N Y N N N N Y N N N Y N N N Y Y Y N N N Y
However, If we only select a sample from persons or friends
whom we can easily access, the answer can be bias

29. Bias in sampling Self-Selection Bias
A bias that occurs because people who feel strongly about a subject are more likely to respond to survey questions than people who feel indifferent about it.

30. Bias in sampling Nonresponse Error
Nonrespondents are People who are not contacted or who refuse to cooperate in the research.
Nonresponse Error is the statistical differences between a survey that includes only those who responded and a perfect survey that would also include those who failed to respond.

31. Bias in sampling Nonresponse Error Example N N N N N N N N N N Y Y Y Y
We are planning to obtain the opinion from 150 people N N N N N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y Y Y N N N N N N Y Y Y Y N N N N N N N N N N N N N N N N Y Y Y Y Y Y N N N N N N N N N N N N N N N N Y Y Y Y N N N N N N N N N N Y Y N N N N N N N N N N N N N N Y Y Y Y Y Y N N N N N N N N N N N Y Y Y Y Y Y
Planned sample: people disagree agree
Actual Sample: 20 people responded people responded
Because many people who disagree did not respond (nonrespondents),
it eventually creates bias in the survey result.