Autocorrelation Analysis
Do draws have "memory"? Are results correlated between draws?
Autocorrelation shows whether the results of draw N are related to draw N-1, N-2, and beyond. If significant autocorrelation is detected, it's a valuable signal for forecasting. If not, it confirms the randomness of the "Премьер" lottery.
Analysis based on 20 draws from to
About Autocorrelation
Mathematical foundations
The autocorrelation function (ACF) measures the linear dependence between values of a time series separated by k steps (lag). In the context of a lottery: is the result of draw N related to the result of draw N-k?
ACF Formula
ACF(k) = Σ(xₜ - x̄)(xₜ₊ₖ - x̄) / [n · Var(x)]
ACF values range from -1 to +1. If |ACF| exceeds the confidence interval ±1.96/√n, the correlation is statistically significant.