least squares

Minimize residual errors

Least squares is a mathematical method for finding the best-fitting curve or line through a set of data points by minimizing the sum of the squared differences between observed values and predicted values.

The technique is fundamental to regression analysis and statistical modeling: We used least squares to fit a trend line to the sales data.

regression

residuals

Ongoing compensation for rebroadcasts

dependent variable · independent variables · outliers · leverage · influence · confidence intervals · diagnostics · normality

fitting

curve fitting

Approximating data mathematically

spline · interpolation · extrapolation · calibration · overfitting · underfitting · degrees of freedom · smoothing

optimization

minimization

Making as small as possible

local minimum · Lagrange multipliers · regularization · constraint

linear algebra

matrix

Ordered numerical arrangement

rank · Gram-Schmidt · LU decomposition · ill-conditioned

statistics

estimator

Sample-based inference rule

hypothesis testing · F-test · t-test · p-value · ANOVA · degrees of freedom · consistency · efficiency

Categories
Opposites
optimization objective

least squaresminimax

Worst-case loss reduction

robustness to outliers

least squaresrobust statistics

Analysis unaffected by outliers

Family

square, least, lessen, lesser, squares, squarely, lessening, squared, lessened

Familiarity
Top 500,000
Profile
Used worldwide · Timeless · Abstract · Rated G