Unit 2: Sampling & data collection
Business Research Methods notes · PTU syllabus (BBA401-18)
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Unit summary
Most research studies a sample rather than a whole population, and good data depends on good collection methods. This unit covers the advantages and limitations of sampling, the sampling process and techniques, sampling and non-sampling errors, primary and secondary data, and observation and survey methods.
After this unit you can
- Explain the advantages and limitations of sampling and the sampling process
- Compare probability and non-probability sampling techniques
- Distinguish sampling and non-sampling errors
- Compare primary and secondary data and observation and survey methods
PTU syllabus topics
- Advantages and limitations of sampling
- the sampling process
- probability and non-probability sampling techniques
- sampling and non-sampling errors
- primary and secondary data collection
- observation and survey methods
Selection
Random, known chance for each unit
Based on judgement or convenience
Examples
Simple random, stratified, cluster
Convenience, quota, snowball
Generalisation
Results can be generalised
Limited generalisation
Cost and time
Higher
Lower
Topic 1
Sampling: advantages and process
Advantages: lower cost, faster results, greater accuracy (fewer non-sampling errors), and possible when the population is huge or testing destroys items. Limitations: sampling error, possible bias and difficulty with very small or heterogeneous populations.
- 1
Define the population
- 2
Identify the sampling frame
List of population units
- 3
Choose the sampling technique
- 4
Decide sample size
- 5
Select the sample
- 6
Collect data
Topic 2
Sampling techniques
Selection
Random, known chance
Based on judgement or convenience
Types
Simple random, systematic, stratified, cluster, multistage
Convenience, judgement, quota, snowball
Generalisation
Possible
Limited
Cost
Higher
Lower
Topic 3
Sampling and non-sampling errors
- Sampling error: the difference between a sample result and the true population value, due to studying only part of the population. It falls as sample size rises.
- Non-sampling errors: arise from other causes — non-response, faulty questionnaires, interviewer bias, wrong recording, processing mistakes. They can occur even in a census.
Topic 4
Primary and secondary data; observation and surveys
| Primary data methods | Secondary data sources |
|---|---|
| Observation | Government publications (Census, RBI) |
| Surveys (personal, telephone, mail, online) | Company records and annual reports |
| Interviews and focus groups | Journals, newspapers, databases |
| Experiments | Websites and industry reports |
Data from
Watching behaviour
Asking questions
Strength
Records actual behaviour, no respondent bias
Collects opinions, attitudes, motives
Weakness
Cannot capture feelings or reasons; costly
Response bias, non-response
Example
Watching shoppers in a store
Online customer satisfaction questionnaire
Key terms
- Sampling frame
- The list from which a sample is drawn
- Sampling error
- Difference between sample and population values
- Non-sampling error
- Errors from collection, response or processing
- Quota sampling
- Non-random sampling filling set quotas
- Observation method
- Collecting data by watching behaviour
Quick revision
- Sampling saves cost and time; needs a good frame.
- Probability: random, systematic, stratified, cluster.
- Non-probability: convenience, judgement, quota, snowball.
- Sampling error falls with sample size; non-sampling errors do not.
Important exam questions
Practice questions written to the PTU exam pattern for this unit's syllabus: short answers (Section A style) and long answers (Sections B and C style).
Short-answer questions
- Q1.State three advantages of sampling.
- Q2.What is a sampling frame?
- Q3.Differentiate between stratified and cluster sampling.
- Q4.Differentiate between sampling and non-sampling errors.
- Q5.State one merit and one limitation of the observation method.
Long-answer questions
- Q1.Explain the sampling process and probability sampling techniques.
- Q2.Explain non-probability sampling techniques with examples.
- Q3.Compare primary and secondary data and their methods of collection.
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