model-validation

Vocabulary Word

Definition

'Model-validation' is the process of confirming that a mathematical or statistical model is accurate. It's like verifying the fitness of a map with the real-world terrain it represents.

Examples in Different Contexts

In data analytics, 'model validation' refers to the techniques used to validate the assumptions, inputs, and outputs of statistical models. An analyst might explain, 'Model validation is crucial for ensuring the reliability of our predictive analyses and decision-making processes.'

Practice Scenarios

Business

Scenario:

We're currently analyzing our risk management strategy, and it's critically important our financial models reflect the true landscape of the market.

Response:

Absolutely, I'll perform model-validation to ensure our risk models are fit for use in real-world scenarios.

Engineering

Scenario:

The prototype design is ready, and we've simulated several critical scenarios. We need to ensure that it will respond as expected.

Response:

I agree. We'll use model-validation to establish the reliability of our simulated scenarios.