What does the term “Least Squares Adjustment” refer to?

The term “Least Squares Adjustment” is primarily associated with a mathematical method that minimizes the sum of the squares of the residuals in a set of measurements. This technique is widely used in geodetic surveys and other fields to provide the most accurate estimates of unknown parameters by fitting a model to observed data.

In practical terms, the method creates a model that predicts values based on a set of observations, and then it adjusts the parameters of that model to reduce the differences between the observed values and the values predicted by the model. These differences, known as residuals, are squared before they are summed, ensuring that both positive and negative discrepancies contribute equally to the total error. Thus, by minimizing this sum, Least Squares Adjustment effectively enhances the precision of the estimated measurements, which is crucial for applications in geodesy, surveying, and other scientific domains.

Other methods mentioned, such as visualizing spatial data, statistical processes for error reduction, or mapping geological features, do not specifically define the scope and application of Least Squares Adjustment as accurately as the correct choice does. However, they may involve elements related to data handling or interpretation, but they do not capture the essence of how parameters are estimated and improved through the specific mathematical framework that Least Squares Adjustment provides