The article discusses the classical concepts of least squares adjustment, a method developed by Gauss. It aims to find the most probable value of a quantity by assuming that the arithmetic mean gives the most likely result and that uncorrelated observations follow a normal distribution. The method also results in the smallest standard error for any symmetrical distribution, even with correlated observations. This makes least squares adjustment a powerful tool for statistical analysis.