Iceland: Lottó
Lottó Autocorrelation Analysis
Lottó: 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 "Lottó" lottery.
Analysis based on 20 draws from to
Max lag:
Draw sums autocorrelation
Correlogram with 95% confidence intervals
20
Observations
0
Significant lags
±0.4383
95% confidence interval
No autocorrelation detected
All ACF values are within the 95% confidence interval. The sequence is statistically random.
ACF(1) for All Numbers
Autocorrelation at lag 1 — quick overview of each number's "memory"
| Ball | ACF(1) | Status |
|---|---|---|
| 1 | -0.1167 | Normal |
| 2 | 0.2069 | Normal |
| 3 | -0.1167 | Normal |
| 4 | 0.0500 | Normal |
| 5 | -0.0553 | Normal |
| 6 | -0.1265 | Normal |
| 7 | -0.1167 | Normal |
| 8 | -0.0553 | Normal |
| 9 | -0.1853 | Normal |
| 10 | 0.0000 | Normal |
| 11 | -0.0553 | Normal |
| 12 | -0.0553 | Normal |
| 13 | -0.2000 | Normal |
| 14 | -0.0611 | Normal |
| 15 | 0.2657 | Normal |
| 16 | -0.0553 | Normal |
| 17 | -0.1853 | Normal |
| 18 | -0.1167 | Normal |
| 19 | -0.1167 | Normal |
| 20 | -0.1167 | Normal |
| 21 | 0.0500 | Normal |
| 22 | -0.0553 | Normal |
| 23 | -0.1853 | Normal |
| 24 | 0.3245 | Normal |
| 25 | -0.0553 | Normal |
| 26 | 0.0500 | Normal |
| 27 | -0.1167 | Normal |
| 28 | -0.0553 | Normal |
| 29 | 0.0000 | Normal |
| 30 | -0.0553 | Normal |
| 31 | -0.1853 | Normal |
| 32 | -0.0553 | Normal |
| 33 | -0.1853 | Normal |
| 34 | -0.0553 | Normal |
| 35 | -0.0611 | Normal |
| 36 | -0.1167 | Normal |
| 37 | 0.0000 | Normal |
| 38 | -0.0167 | Normal |
| 39 | -0.2687 | Normal |
| 40 | -0.0553 | Normal |
| 41 | 0.1125 | Normal |
| 42 | -0.1853 | Normal |
| 43 | -0.1853 | Normal |
| 44 | -0.0553 | Normal |
| 45 | -0.1167 | Normal |
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.