stochastic VS random

• random
  With random process, the same probability is assigned to all outcomes because each outcome has an equal chance of occurring. Typical examples of random processes include drawing a card from a deck, rolling a die, or tossing a coin. In a geographic context, an ornithologist might develop a GIS model to predict breeding bird occupancy within a wildlife refuge by assigning all nesting locations an equal random probability for occupancy.

• stochastic
  With stochastic process, the likelihood or probability of any particular outcome can be specified and not all outcomes are equally likely of occurring. For example, an ornithologist may assign a greater probability that a bird will select a nesting location based on how far it is from the edge of the refuge or whether the location is shielded by a dense tree canopy.