When data sources conflict, what is a best practice for resolving the conflict?

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Multiple Choice

When data sources conflict, what is a best practice for resolving the conflict?

Explanation:
When data sources conflict, the best practice is to review all sources, seek additional data, consider environmental factors, and integrate findings before drawing conclusions. This approach embodies triangulation in data-based decision making: it uses multiple lines of evidence to cross-check results, reducing the risk that a single report or a biased view drives decisions. It also acknowledges context—such as timing, setting, and conditions—that can explain discrepancies. Instead of favoring the most favorable report, ignoring conflicts, or discarding data, you gather more information, examine the methods and reliability of each source, and synthesize what all the data collectively indicate before deciding on an intervention or conclusion.

When data sources conflict, the best practice is to review all sources, seek additional data, consider environmental factors, and integrate findings before drawing conclusions. This approach embodies triangulation in data-based decision making: it uses multiple lines of evidence to cross-check results, reducing the risk that a single report or a biased view drives decisions. It also acknowledges context—such as timing, setting, and conditions—that can explain discrepancies. Instead of favoring the most favorable report, ignoring conflicts, or discarding data, you gather more information, examine the methods and reliability of each source, and synthesize what all the data collectively indicate before deciding on an intervention or conclusion.

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