Final answer:
Validating data should occur when inconsistencies between subjective and objective data are noticed. Ensuring data reliability and validity is essential, involving a critical evaluation of sources, checking for bias, and verifying alignment with established scientific practices.
Step-by-step explanation:
Validating data is a critical process in scientific inquiry. It involves ensuring that the data collected is both reliable and valid. Reliability refers to the consistency of the data over time and across different observers or instruments. In contrast, validity is about the accuracy and truthfulness of the data in representing what it is supposed to represent.
When subjective data (personal observations or opinions) and objective data (those measured and observed directly) do not seem to agree, or do not make sense together, it is essential to critically evaluate the data sources. Examine the evidence supporting the information, look for possible bias, and consider the expertise and motives of the person providing the data. It's also useful to compare the claim against other researchers’ views and ensure the data collection methods have been scientifically justified. By doing so, you can determine if the data collection methods need to be adjusted or the data interpreted differently.
Validating data should occur as soon as inconsistencies are noticed, and continue throughout the data analysis process. Applying critical thinking and skepticism during data analysis will help in providing objective evidence to support scientific claims and ensure the integrity of the research findings.