Data Collection Methods Quiz

Data Collection Methods

• Primary Data: Information gathered directly, using methods like surveys and interviews, can be quantitative or qualitative.
• Secondary Data: Pre-existing data from sources like records, publications, or the internet.
• Personal Interviews: Advantages include clarifying doubts and capturing nonverbal cues; disadvantages are high cost and time commitment, plus potential for response bias.
• Telephone Interviews: Less costly than in-person interviews, but lack of nonverbal cues and limited length are drawbacks.
• Self-Administered Surveys: Low cost and broad reach are advantages; disadvantages are low response rates and lack of opportunities to clarify questions.
• Questionnaire Design Principles: Include all research constructs using both objective and subjective questions.
• Response Formats: Use closed or open-ended questions depending on needs.
• Question Wording: Avoid biased, double-barreled, ambiguous, or recall-based questions to ensure accuracy.
• Question Sequence: Place sensitive questions toward the end.
• Personal Data: Collect demographics cautiously, avoiding overly invasive questions initially.
• Cover Letter: Should include an introduction, a statement about confidentiality, and motivation to encourage participation.
• Observational Studies: Can be structured or unstructured, but may be subject to bias.
• Focus Groups: Facilitated discussions used to gain insights and gather data.

Sampling

• Sampling: The selection of a subset of a population to study, allowing for generalization to the wider population.
• Advantages of Sampling: Lower cost, faster, and fewer risks than studying the whole population.
• Key Terms: Population (entire group), sample (subset), sampling units, and subjects.
• Sampling Techniques: Probability and non-probability sampling.
• Probability Sampling: Implies equal selection chance; examples include simple random, stratified, systematic, and cluster sampling.
• Non-Probability Sampling: Unequal selection chance—convenience, quota, and judgment sampling are its methods.
• Parameters vs. Statistics: Parameters describe populations, and statistics describe samples.
• Sampling Process: Define the population, create a sampling frame, and choose a sampling design and sample size.
• Simple Random Sampling: Every member has an equal chance of being chosen.
• Systematic Sampling: Choose every nth member of a population.
• Stratified Sampling: Divide the population into strata (groups) and sample from each.
• Cluster Sampling: Divide the population into clusters and sample from selected clusters.
• Convenience Sampling: Selecting participants based on ease of access.
• Judgment Sampling: Researcher selects participants based on their judgment.
• Quota Sampling: Selecting participants to match a specific proportion or quota characteristics.
• Sample Size Guidelines (General): Typically between 30 and 500.
• Sample Size Guidelines (Experiments): Ideally 15-20 participants per condition.

Test your knowledge on various data collection methods including primary and secondary data, personal interviews, and self-administered surveys. This quiz covers the principles of questionnaire design and the advantages and disadvantages of different methods. Enhance your understanding of effective data gathering techniques.