Unit 2: Sampling and measurement
Business Research Methods notes · PTU syllabus (MCOP203-18)
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Unit summary
Good research depends on whom you study and how you measure. This unit covers census vs sampling, probability and non-probability sampling methods, sample size and errors, uni-dimensional and multidimensional scales, levels of measurement, rating, ranking, Likert and semantic differential scales, and data editing, coding, classification and tabulation.
After this unit you can
- Distinguish census and sampling and explain sampling methods
- Explain sample size and sampling and non-sampling errors
- Explain levels of measurement and scaling techniques
- Explain editing, coding, classification and tabulation of data
PTU syllabus topics
- Census vs sampling
- probability and non-probability sampling methods
- sample size and errors
- uni-dimensional and multidimensional scales
- nominal/ordinal/interval/ratio measurement
- rating/ranking/Likert/semantic differential scales
- data editing
- coding
- classification and tabulation
Likert
Agreement on a 5 or 7-point scale
Semantic differential
Between bipolar adjectives
Rating scales
Graphic or itemised
Ranking
Order of preference
Stapel
−5 to +5 around one adjective
Topic 1
Census vs sampling
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
Levels of measurement
Nominal
Labels or categories only
Gender, city, brand used
Ordinal
Order or rank
Rank of brands, education level
Interval
Equal intervals, no true zero
Temperature in °C, rating scales
Ratio
Equal intervals and a true zero
Income, age, sales
Higher levels allow more statistical analysis: mode for nominal, median for ordinal, mean for interval and ratio.
Topic 5
Scaling techniques
Comparative: paired comparison
Choose between two at a time
Comparative: rank order
Rank several items
Comparative: constant sum
Divide 100 points among items
Non-comparative: Likert
Agreement on a 5- or 7-point scale
Non-comparative: semantic differential
Between bipolar adjectives (cheap–expensive)
Non-comparative: Stapel and graphic rating
−5 to +5, or a marked line
Example
Likert item: "The staff were helpful." Strongly disagree (1) — Disagree (2) — Neutral (3) — Agree (4) — Strongly agree (5).
Uni-dimensional vs multidimensional scaling
- Uni-dimensional scales measure one attribute (satisfaction with service speed) — Likert, Thurstone, Guttman.
- Multidimensional scaling (MDS) represents perceptions of objects on several dimensions simultaneously as a perceptual map (brands positioned by price and quality).
Topic 6
Editing and coding
- Editing checks completed questionnaires for completeness, consistency, accuracy and legibility. Field editing happens soon after collection; central editing is done in the office.
- Coding assigns numbers to answers so they can be counted and analysed (Male = 1, Female = 2; Strongly agree = 5). A codebook records every code.
- Classification groups data into categories; tabulation arranges it in tables.
Topic 7
Classification and tabulation
- Classification: arranging data into groups by common characteristics — geographical, chronological, qualitative (attributes), quantitative (class intervals).
- Tabulation: presenting classified data in rows and columns; parts — table number, title, head note, captions, stubs, body, footnote, source.
- Types: simple (one characteristic), complex (two-way, three-way), general purpose and special purpose tables.
Exam tip
Well-tabulated data make analysis easy — always title tables and mention units and sources.
Key terms
- Census
- Study of every unit in the population
- Sampling frame
- List of population units from which a sample is drawn
- Non-sampling error
- Error from data collection, processing or response
- Likert scale
- Agreement scale, usually five points
- Coding
- Assigning numbers or symbols to responses
Quick revision
- Probability: simple random, systematic, stratified, cluster, multi-stage.
- Non-probability: convenience, judgement, quota, snowball.
- Errors: sampling (reduce with larger n) vs non-sampling.
- Scales: nominal, ordinal, interval, ratio; Likert, semantic differential, rating, ranking.
- Editing → coding → classification → tabulation.
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.Distinguish census and sample survey.
- Q2.What is stratified sampling?
- Q3.What is snowball sampling?
- Q4.Distinguish interval and ratio scales.
- Q5.What is a semantic differential scale?
- Q6.What is tabulation?
Long-answer questions
- Q1.Explain probability and non-probability sampling methods.
- Q2.Explain sampling and non-sampling errors and determinants of sample size.
- Q3.Explain levels of measurement and scaling techniques.
- Q4.Explain editing, coding, classification and tabulation of data.
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