Error terms

Error terms in statistics refer to the differences between observed data and the predictions or models made based on that data. They represent the discrepancy or deviation that cannot be perfectly explained by the model. Essentially, errors capture the randomness, variability, or unforeseen factors influencing the data that the model does not account for. Understanding these errors helps in assessing the accuracy and reliability of the model, guiding improvements and ensuring better predictions in future analyses.