Final answer:
True, finding errors during verification is an indicator to revisit the data cleaning process to correct any inaccuracies. Experts use their initial expectations to spot errors and variations in analysis results prompt the need for data reevaluation. It's essential to consider uncertainties and errors inherent in data sources and instruments.
Step-by-step explanation:
True: If errors are found during the verification process, it indeed signals the need to return to the data cleaning process to rectify the issues. This is a critical step in ensuring data accuracy and reliability. Experts are often guided by their initial sense of what the correct answer should be, using it as a benchmark to compare against actual results. Such comparisons can reveal discrepancies that necessitate a reexamination of the data or the methods employed in collecting it.
Variations in results of data analysis among different individuals working on the same data set should trigger a review of the data collection and cleaning procedures. Furthermore, it is important to note that it is common for numbers extracted from graphs to have uncertainties; if these numbers differ from expected values, they need to be assessed to ensure they fall within the estimated data extraction uncertainties.
Repetition of experiments and data gathering is essential to verify results, as stated in the principle of thorough testing. Finally, in any research or data analysis, awareness of sampling errors and nonsampling errors is crucial for accuracy. Defective instruments, for instance, can cause nonsampling errors, so these must be accounted for when cleaning data.