Market Research- Topic 7

What is a population in marketing research?

All elements sharing common characteristics relevant to the research problem.

What is a census?

A survey including all elements of a population.

What is a sample?

A subgroup of the population selected for the study.

What are sample characteristics called?

Statistics.

What are population characteristics called?

Parameters.

What are the 5 steps of sampling?

Step 1 — Define the Target Population

Step 2 — Determine the Sampling Frame

Step 3 — Select a Sampling Technique

Step 4 — Determine Sample Size

Step 5 — Execute the Sampling Process

Step 1

What is the target population?

The group of elements possessing the information needed by the researcher.

Step 1

What does defining the target population require?

A precise statement of who is included/excluded.

Step 2

What is a sampling frame?

A list or device identifying all elements of the target population. Examples: telephone book, mailing list, directory.

Step 3

What are the two main categories of sampling techniques?

Non‑probability and probability sampling.

Step 4

What is sample size?

The number of elements included in the study.

Step 4

What factors influence sample size?

Nature of research, number of variables, previous studies, etc.

Step 5

What does executing the sampling process involve?

Implementing all previous sampling decisions.

What is convenience sampling?

Selecting respondents who are easily accessible.

Main limitation of convenience sampling?

Not representative of the population.

What is judgemental sampling?

Researcher selects elements they believe are representative.

Limitation of judgemental sampling?

Results cannot be generalized.

What is quota sampling?

A two‑stage judgemental sampling method using control characteristics (quotas).

What is the purpose of quotas?

To match the sample composition to the population.

What is snowball sampling?

Initial respondents refer additional respondents who share target characteristics.

When is snowball sampling useful?

When the target population is hard to locate.

What is simple random sampling (SRS)?

Each population element has a known and equal chance of selection.

Main advantage of SRS?

Results can be projected to the population.

Main limitation of SRS?

Difficult to construct a sampling frame.

What is systematic sampling?

Selecting every i-th element after a random start.

How is the sampling interval calculated?

N/n (population size / sample size).

What is stratified sampling?

Dividing the population into homogeneous strata and sampling each via SRS.

What are stratification variables?

Variables used to form strata (e.g., demographics, customer type).

Key advantage of stratified sampling?

Ensures representation of important subgroups.

What is cluster sampling?

Dividing the population into heterogeneous clusters and randomly selecting clusters.

Difference between one‑stage and two‑stage cluster sampling?

One‑stage: all elements in selected clusters are sampled.

Two‑stage: a sample of elements is drawn from each selected cluster.

Main advantage of cluster sampling?

Lower cost and greater feasibility.

What confidence level is used in the sample size table?

95%.

What assumption is made about p and q?

p = q = 0.5.

What should the researcher do when selecting field workers?

Develop job specifications, define desired characteristics, recruit suitable individuals.

Why is training critical?

Ensures uniform administration of the questionnaire.

What does training cover?

• Making initial contact

• Asking questions properly

• Probing

• Recording answers

• Terminating the interview

What is the purpose of supervision?

Ensuring procedures are followed correctly.

What does supervision involve?

• Quality control

• Sampling control

• Cheating control

• Central office control

What is validation?

Verifying that interviews are authentic.

How is validation done?

Contacting 10–25% of respondents.

What criteria are used to evaluate field workers?

Cost/time, response rates, interviewing quality, data quality.