What type of data does the method of least squares typically deal with?

The method of least squares is primarily used with quantitative data, which consists of numerical values that can be measured and analyzed statistically. This method is commonly applied in regression analysis, where the goal is to find the best-fitting line or curve that describes the relationship between two or more variables. Quantitative data enables mathematical operations and calculations that are central to the least squares process, such as finding the sum of squared differences between observed values and values predicted by a model.

In contrast, qualitative data refers to non-numerical categories or characteristics, which cannot be subjected to mathematical manipulation in the same way. Categorical data is a subset of qualitative data that groups observations into distinct categories without any natural order, while ordinal data, another subset, involves categories with a defined order but without consistent intervals. Since these types of data do not provide the numerical relationships necessary for the least squares method, they are not applicable for this technique. Thus, the method of least squares focuses on quantitative data, making it the correct answer.