Why is the normal probability plot preferred in statistics?

The normal probability plot is preferred in statistics primarily because it visually confirms the normality of the dataset. This type of plot displays the observed values of a dataset against the expected values if the data were perfectly normally distributed. When the points on this plot form approximately a straight line, it indicates that the dataset follows a normal distribution. This visual assessment is crucial for many statistical analyses that assume normality, allowing researchers to quickly evaluate whether their data meets this assumption.

Furthermore, the visual nature of the normal probability plot offers an intuitive way to assess normality, alongside or instead of statistical tests, which may not be as straightforward to interpret. By identifying deviations from linearity in the plot, statisticians can also detect skewness or the presence of outliers, which further enhances their understanding of the data distribution.