Final answer:
The major types of causal models used for forecasting include deterministic, statistical, empirical, and analytical models, each varying in their approach to predict future events or trends based on different principles such as precise determination, probability, observation, and complex statistical analysis.
Step-by-step explanation:
The major types of causal models used for forecasting include deterministic models, statistical models, empirical models, and analytical models. Deterministic models are often used when one value precisely determines another, such as in the case of predicting a rocket’s thrust to achieve orbit. Statistical models, on the other hand, are used to describe probabilities and alternative outcomes, exemplified by weather forecasts that tell us the likelihood of rain. Empirical models are based on observations and are often used despite a less comprehensive understanding of the underlying system, as in the case of predicting crop growth based on temperature changes. Lastly, analytical models are deemed ecologically realistic and involve complex statistical techniques like regression analysis to measure relationships between cause and effect variables, thereby allowing for a more nuanced understanding of phenomena such as the impact of various factors on obesity.