When Good Data Go Bad: Detecting Data Quality Problems Before You Analyze
“Garbage in, garbage out.” It’s one of the oldest sayings in statistics, and for good reason. Even the most sophisticated statistical methods cannot rescue poor-quality data. Before choosing a statistical test, fitting a regression model, or creating your first graph, it is essential to ensure that your data accurately represent what you intended to measure. Data quality issues are surprisingly common. They can arise during data collection, data entry, data transfer, or data management. Left undetected, these problems can…