Least Squares
Least squares is a mathematical method used to find the best-fitting line or curve for a set of data points. Imagine you have several points on a graph representing measurements or observations; least squares helps determine a line that minimizes the distance between the line and all the points. This means it finds a line that is as close as possible to all the points, reducing the overall error. It’s commonly used in statistics and data analysis to make predictions and understand relationships between variables.
Additional Insights
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Least squares is a statistical method used to find the best-fitting line or curve for a set of data points. Imagine you have a scatter plot of points, and you want to draw a straight line that comes as close as possible to all of them. Least squares calculates the line by minimizing the sum of the squares of the distances (errors) between each data point and the line. This helps in predicting values and understanding relationships in the data, commonly used in fields like finance, science, and engineering.