method of least squares
The method of least squares is a statistical technique used to find the best-fitting line through a set of data points. It works by minimizing the differences between the observed values (the actual data) and the values predicted by the line. Essentially, it calculates the line that has the smallest possible sum of the squares of these differences, often called "errors." This approach is widely used in various fields, including economics and engineering, to make predictions and understand relationships between variables by providing a clear, mathematical representation of the data trend.
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The method of least squares is a statistical technique used to find the best-fitting line or curve for a set of data points. It works by minimizing the differences between the actual data points and the values predicted by the line or curve. Essentially, it adjusts the line or curve so that the overall distance (or errors) between the predicted values and the observed values is as small as possible. This method is widely used in fields like economics, engineering, and science for making predictions and understanding relationships in data.