What is Testing

1.

Involves using the calibrated simulation to make predictions on a particular time period (or cross section) from which the data has not been used for calibrations. These predictions are then compared with the corresponding data to ensure the goodness of fit of simulated data with real data. Note that the data being used here is not the same as the one used for calibration. The testing exercise provides further validity of the models and ensures a degree of robustness for practical use. Learn more in: Modelling of Consumer Goods Markets: An Agent-Based Computational Approach

2.

It is process of making a machine learning model to test the unknown sample from testing datasets for the predictions. Learn more in: Risk Analysis of Diabetic Patient Using Map-Reduce and Machine Learning Algorithm

3.

The use of measurement to support inferences about students’ knowledge, skills, or abilities. Learn more in: Self- and Peer-Assessments in the Iranian Context: A Systematic Review