Statistical models are nondeterministic, implying that the outputs are not entirely determined by specifications. Hence, the same input can produce different outcomes when various statistical tests/runs are used. For example, using the same data, you can produce different statistical results of correlation (Spearman's correlation and Pearson's correlation)
Conversely, mathematical models are deterministic and always give the same output, provided that the initial and boundary conditions are the same.