Data Collection Methods Quiz

Study Notes

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.

Description

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.