Which of the following can skew data due to assumptions?

Human interaction in the data process can skew data due to assumptions because individuals may bring their own biases, interpretations, and judgments into the data handling and analysis phases. When humans interact with data, decisions on how to categorize, clean, and interpret that data can be influenced by personal experiences or preconceived notions, leading to distorted results. This is particularly critical in situations where subjective assessment plays a role in determining data quality or relevance.

For instance, if a person assumes a certain trend or relationship exists based on their experience, they might unconsciously alter the data analysis or interpretation to support that assumption. This can prevent an objective view of the data and lead to conclusions that do not accurately reflect reality.

In contrast, technical errors in software typically stem from bugs or glitches rather than assumptions and are generally more quantifiable and straightforward to address. A reduction in workforce might affect data handling capacity or availability but does not inherently skew the data itself through assumption. Increased customer inquiries might lead to changes in data volume or collection but do not involve assumptions that would skew the analysis in the same direct way that human interaction does.