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 "Lotto 6/42" 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.