The problem of predicting future cycles of the sunspot number is physically significant. Recently, a number of authors have made complex systems analyses (''chaos'') of the set of monthly Wolf sunspot numbers. Each of these analyses revealed the presence of low-dimensional deterministic behavior, and some of the papers applied the techniques of nonlinear prediction to predict future sunspot numbers. All of these papers analyzed filtered or smoothed sunspot number sets derived from the monthly Wolf sunspot numbers. Here, we have performed the same type of analysis on the raw (e.g., unfiltered) monthly sunspot number data set and on data sets derived from it, in particular, an ''unrectified'' set with a 22-year period. We find no evidence that the sunspot numbers are generated by a low-dimensional deterministic nonlinear process; further, by considering suitably constructed surrogate data sets (Theiler et al., 1991), we show that filtering techniques can give some spurious evidence for the presence of deterministic nonlinear behavior. Consequently, any predictions based on the assumption of such a process are not significantly better than those from linear stochastic models (Casdagli, 1991). ¿ American Geophysical Union 1992