Why do models have missing information?

Answer 1

Because it is impossible to have complete information about any system. Heisenberg's Uncertainty Principle and chaos theory, among other things, ensure that it is impossible to know everything about any system.

Answer 2

Models may have missing information either because the data collection process was incomplete or due to variables that were not available at the time of data gathering. It is important to address missing data to prevent biases in the model and improve its accuracy and reliability. Techniques like imputation or using algorithms that can handle missing data, such as tree-based models, can help mitigate the impact of missing information on the model's performance.

Answer 3

All models are simplifications.