Least squares estimation is a statistical method used to determine the best-fitting line or curve for a set of data points. It minimizes the sum of the squares of the differences between the observed values and the values predicted by the model. This technique is commonly applied in regression analysis to find relationships between variables. The least squares method is particularly useful in linear regression, where it helps to estimate the coefficients of the linear equation. By minimizing the squared errors, it provides a way to quantify how well the model represents the data, making it easier to make predictions and analyze trends.