The article explores how rounding errors can affect tests for normality in measurement data. By analyzing real data, the researchers show that ignoring rounding errors can lead to incorrect conclusions about whether the data follows a normal distribution. They demonstrate that the distribution of test statistics changes based on the ratio of rounding errors to measurement error standard deviation, especially for larger sample sizes. This study highlights the importance of considering rounding errors in statistical analysis to ensure accurate results.