Missing values

In statistics, missing values are a common occurrence. Several statistical methods have been developed to deal with this problem. Missing values mean that no data value is stored for the variable in the current observation. Modern statistical packages made dealing with missing values much easier.
See more at Wikipedia.org...

Values of variables within data sets which are not known. Although such cases that contain missing data are incomplete, they can still be used in data analysis. Various methods exist to substitute missing data (e.g., by mean substitution, various types of interpolations and extrapolations). Also, pariwise deletion of missing data can be used. See also, Pairwise deletion of missing data, Casewise (Listwise) deletion of missing data, Pairwise deletion of missing data vs. mean substitution, and Casewise vs. pairwise deletion of missing data.