Dealing with missing data is frequently necessary in social sciences research. There are many statistical methods for dealing with missing data. This paper focuses on four of the more basic methods: (1) listwise deletion; (2) pairwise deletion; (3) total mean substitution; and (4) variable mean substitution. Each of the methods is discussed, and the discussion includes instruction on how to perform the technique using the Statistical Package for the Social Sciences (SPSS). Information is also provided on how to write an SPSS syntax file to perform variable mean substitutions. A heuristic data set of 11 individual surveys, each of which contains 20 questions, is used to make the discussion concrete and optimally useful. Three appendixes illustrate determining the variables to delete, deleting some cases and determining means, and performing the mean substitution. (Contains four tables and seven references.) (Author/SLD)