You're at odds with colleagues over data privacy in statistical analysis. How do you find common ground?
Navigating disagreements with colleagues over data privacy in statistical analysis can be tricky, but prioritizing collaboration and transparency can help. Here's how to find common ground:
What strategies have you found effective for resolving such conflicts?
You're at odds with colleagues over data privacy in statistical analysis. How do you find common ground?
Navigating disagreements with colleagues over data privacy in statistical analysis can be tricky, but prioritizing collaboration and transparency can help. Here's how to find common ground:
What strategies have you found effective for resolving such conflicts?
-
In my Experience I prefer we look at the issue holistically, where by we consider all the factors involve and how we best understand it as it relate to each data set and how its been perceived when we let it out. when we have all come to terms on what we know and what we need to know it gives a better platform to resolve the differences.
-
If anybody is not committed to basic standards of privacy, should not be in the business of data collection and analysis, business. Privacy is the bedrock of the data business, respondents share data under the implicit agreement that privacy will be maintained. If one breaches the agreement or not in a position to accept this implicit agreement, the project should be terminated, audit has to be done to ascertain where all the data resides, and the data should be deleted, or destroyed depending on the medium.