Final answer:
Valid data must be accurate, representative, relevant, and significant, aligning closely with the research topic. Data should be reliable to be considered valid, ensuring consistency and dependability in the results.
Step-by-step explanation:
Valid data are accurate, representative, relevant, and significant. When we discuss valid data in research or data collection, we are referring to information that is pertinent and directly related to the topic of the study. This makes it crucial for the data to be closely aligned with the research objectives or hypotheses.
In addition to being relevant, data should also be reliable, providing consistent results over repeated tests or observations, and valid, accurately reflecting the concept they are intended to measure. Lastly, the data should be significant, meaning that it has a meaningful impact on the research questions and leads to valid conclusions.
To assess if a measurement is considered relevant to the topic of the study, option B (sociological) and D (quantitative) are immediately incorrect, as they do not pertain directly to the nature of the data in relation to its subject. Option C (valid) is close but does not specifically denote the data's pertinence to the topic. Therefore, the most appropriate choice is A (reliable), which means that the measurement yields consistent results across multiple observations and is dependable.