Wrong use of averages implies wrong results from many heuristic models
In a linear world, averages make perfect sense. Something too big is compen-sated by something too small. We show, however that the underlying diffe-rential equations (e.g. unlimited growth) rather than the equations them-selves (e.g. exponential growth) need to be linear. Especially in finance and economics non-linear differential equations are used although the input pa-rameters are average quantities (e.g. average spending). It leads to the sad conclusion that almost all results are at least doubtful. Within one model (diffusion model of marketing) we show that the error is tremendous. We al-so compare chaotic results to random ones. Though these data are hardly dis-tinguishable, certain limits prove to be very different. Implications for finance can be important because e.g. stock prices vary generally, chaotically, though the evaluation assumes quite often randomness.