Statistical Analysis System (SAS) Programming Certification Practice Exam 2025 – The All-in-One Guide to Master Your Certification!

SAS handles missing values in calculations by generally excluding them from the computations. When performing statistical analyses or arithmetic calculations, any observations that have missing values for the relevant variables are typically not included in the calculation. This means that when you calculate means, sums, or other statistical measures, SAS will only consider the non-missing values.

For example, if you are calculating the average of a series of numbers and some of those numbers are missing, SAS will ignore those missing values in the calculation of the average. This behavior helps to ensure that the results reflect only the available data, which is critical in maintaining the integrity and accuracy of the analysis.

While there are methods to explicitly handle missing values, such as using imputation, by default SAS does not substitute them with zero or include them in calculations unless instructed to do so. Thus, this approach helps when interpreting data analyses and maintaining clarity around the influence of missing data on statistical outcomes.