# Introduction In this challenge, we will implement a function in Python that solves Ordinary Least Squares (OLS) for a given set of sample data. OLS is commonly used in machine learning, particularly in linear regression, to find the best-fitting parameters for a linear equation. The function will take two lists of sample values, corresponding to the independent variable and the dependent variable, and return the rounded parameters for the linear equation. The implementation should adhere to certain requirements, such as using Python 3 without any standard or third-party libraries.
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