Primary Data

Rationale: Primary data refers to first-hand information collected by the researcher specifically for the current research problem through direct fieldwork, surveys, or observations.

Rationale: Even if mailed or self-administered, data gathered directly from respondents via a questionnaire designed for the study is considered primary data.

Rationale: Stratified random sampling divides the heterogeneous population into homogeneous subgroups or strata, ensuring adequate representation of all segments.

Rationale: Interview schedules allow the interviewer to explain ambiguous questions and generally result in a much higher response rate compared to mailed questionnaires.

Rationale: Participant observation and open-ended interviews yield rich qualitative primary data necessary for understanding complex cultural and traditional systems.

Rationale: A pilot survey is a small-scale preliminary test of the questionnaire and field methodology to identify and correct flaws before full-scale deployment.

Rationale: Snowball sampling relies on referrals from initial subjects to generate additional subjects, making it ideal for hard-to-reach or hidden populations.

Rationale: Ground truthing involves on-site primary data collection to check the accuracy of interpretations made from aerial photos or satellite imagery.

Rationale: Leading questions hint at the desired answer, introducing systematic bias and compromising the validity of primary data.

Rationale: Likert scales measure attitudes (e.g., Strongly Agree to Strongly Disagree) which represent ordered categories, forming an ordinal scale of measurement.

Rationale: Systematic sampling selects elements at regular intervals (every k-th unit) from a sampling frame or spatial grid, ensuring even geographical coverage.

Rationale: Primary data collection requires significant time, financial investment, and meticulous control over various forms of bias.

Rationale: Measuring river discharge directly in the field yields numerical values measured first-hand, making it primary quantitative data.

Rationale: Sampling error is the natural discrepancy between a sample estimate and the true population value arising from examining only a subset of the population.

Rationale: Depth or unstructured interviews provide maximum flexibility, allowing respondents to share rich narrative primary data.

Rationale: Counting vehicles directly at intersections generates fresh, first-hand observational primary data regarding traffic flow.

Rationale: A sampling frame is the operational list, directory, or map of the entire target population from which a sample is selected.

Rationale: Recall bias occurs when study participants do not accurately remember past actions, experiences, or timeline details, affecting survey validity.