Data Science #27 - The History of Least Squares (1877) – Data Science Decoded

Mansfield Merriman's 1877 paper traces the historical development of the Method of Least Squares, crediting Legendre (1805) for introducing the method, Adrain (1808) for the first formal probabilistic proof, and Gauss (1809) for linking it to the normal distribution.

He evaluates multiple proofs, including Laplace’s (1810) general probability-based derivation, and highlights later refinements by various mathematicians.

The paper underscores the method’s fundamental role in statistical estimation, probability theory, and error minimization, solidifying its place in scientific and engineering applications.

Poddgruvan

Data Science #27 - The History of Least Squares (1877)

Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985)

Data Science #33 - The Backpropagation method, Paul Werbos (1980)

Data Science #32 - A Markovian Decision Process, Richard Bellman (1957)

Data Science #31 - Correlation and causation (1921), Wright Sewall

Data Science #30 - The Bootstrap Method (1977)

Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979)

Data Science #28 - The Bloom filter algorithm

Data Science #26 - The First Gradient decent algorithm by Cauchy (1847)

Data Science #24 - The Expectation Maximization (EM) algorithm Paper review (1977)

Data Science #23- The Markov Chain Monte Carl MCMC Paper review (1953)