You're faced with doubts about your analytical approach. How can you defend its validity?

When confronted with doubts about your analytical approach, one effective strategy to defend its validity is to emphasize the robustness of your methodology. Highlight the thoroughness of your data collection process, ensuring it encompasses diverse sources and is meticulously documented. Stress the application of recognized analytical frameworks or industry standards that underpin your approach, demonstrating alignment with best practices. Lastly, showcase how your conclusions are supported by clear, logical reasoning derived from the data, reinforcing the integrity of your findings. This approach not only bolsters confidence in your analysis but also validates its reliability amidst scrutiny.

Always document each step of data cleaning and transformation. This transparency helps others understand your process and trust your results. For Example: In a sales analysis project, we sourced data from a reputable CRM. We then cleaned the data by removing duplicate entries and correcting inconsistent formatting. Each step was documented to maintain transparency and ensure the reliability of our analysis.

A robust analysis is critical to have confidence in any data. A lab should have thoroughly validated the measurement approach, considered any biases in the approach, and established uncertainty levels of the measurement approach. After validation, measurements following the same procedure as the validated procedure should be recorded, preferably with a number of replicates. Where possible, quality control samples should be included to ensure the instrumentation is performing as expected.

You should also stress-test your analysis - run scenarios through the model/analysis to see if the method falls apart under certain conditions or assumptions. This, more than anything, I believe, will expose if your approach is flawed due to some bias.