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Data Collection Methods

Research Methodology · BCA · Updated Apr 23, 2026

Table of Contents

Data Collection Methods

Data collection is the systematic gathering of information to answer research questions. Methods are classified as primary (original data) or secondary (existing data). The choice depends on research objectives, design, resources, and population.

Primary Data Sources

Primary data is collected directly by the researcher through surveys, experiments, interviews, observations, or focus groups. It is specific to the research problem but more expensive and time-consuming to gather.

Questionnaires

A questionnaire is a structured set of questions. Closed-ended questions (Likert scale, multiple choice, yes/no) are easy to analyse. Open-ended questions provide richer data but are harder to code. Good questionnaires are clear, unbiased, logically ordered, and pilot-tested.

Interviews

Interviews can be structured (fixed questions), semi-structured (guided but flexible), or unstructured (conversational). They provide depth and allow probing. Challenges include interviewer bias, time cost, and difficulty in quantifying responses.

Observation

Observation records behaviours directly. Participant observation involves the researcher joining the group. Non-participant observation is external. Observation captures actual behaviour but may be affected by the Hawthorne effect (behaviour change when observed).

Secondary Data

Secondary data comes from existing sources: government statistics, published research, organisational records, and online databases. It saves time and cost but may not perfectly fit the research needs. Source credibility and timeliness must be evaluated.

Sampling

Sampling selects a subset of the population for study. Probability sampling (random, stratified, cluster, systematic) gives every member a known chance of selection. Non-probability sampling (convenience, purposive, snowball, quota) is easier but less generalisable. Sample size affects precision.

Measurement and Scales

Measurement assigns values to variables using scales: nominal (categories), ordinal (ranked), interval (equal intervals, no true zero), and ratio (equal intervals, true zero). The scale type determines which statistical analyses are appropriate.

Summary

Effective data collection requires choosing appropriate methods, designing good instruments, sampling correctly, and understanding measurement levels. The quality of data directly determines the validity of research findings.

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