Sampling in computational modeling refers to the process of selecting a subset of individuals, items, or data points from a larger population or dataset to estimate characteristics or behaviors of that population. This technique is widely utilized across various fields such as statistics, machine learning, and simulation. Here are some key aspects and types of sampling relevant in computational modeling: 1. **Purpose of Sampling**: - **Estimation**: To infer properties of a population based on a smaller sample.
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