Aim

The aim of this experiment is to perform regression and curve fitting on a given dataset using numerical approximation methods and analyze the accuracy of the fitted model.

Specifically, the objectives include:

1. To apply the Least-Square Method for estimating the best-fit curve that minimizes the sum of squared errors between observed and predicted values.
2. To implement the Weighted Least-Square Method to handle data with varying levels of importance or measurement accuracy.
3. To generate predictive mathematical models that represent the underlying trend of the dataset.
4. To visualize the fitted curve against the actual data points for interpretation and validation.
5. To understand the importance of curve fitting techniques in engineering, science, and data-driven decision making.