Table 3 Comparison of linear and non-linear regression analysis of changes in running speeds across years in the annual ten fastest women and men to determine which model is the best
From: Will women outrun men in ultra-marathon road races from 50 km to 1,000 km?
Running speed | Kind of regression | Sum of squares | DOF | AICc | Best regression | Best regression | Delta | Probability | Likelihood |
|---|---|---|---|---|---|---|---|---|---|
AIC-Test | F-Test | ||||||||
Annual ten fastest men 50 km | Polynomial | 29.00 | 16 | 61.73 | Linear | Linear | 33.98 | 4.16 e-08 | 100% |
linear | 71.73 | 31 | 27.75 | ||||||
Annual ten fastest women 50 km | Polynomial | 5.87 | 22 | -31.64 | Polynomial | Polynomial | 8.34 | 0.015 | 98.5% |
Linear | 9.02 | 23 | -23.30 | ||||||
Annual ten fastest men 100 km | Polynomial | 3.08 | 39 | -107.90 | Polynomial | Polynomial | 88.13 | 7.28 e-20 | 100% |
Linear | 26.76 | 42 | -19.77 | ||||||
Annual ten fastest women 100 km | Polynomial | 9.57 | 32 | -41.00 | Polynomial | Polynomial | 34.71 | 2.89 e-08 | 100% |
Linear | 27.52 | 33 | -6.29 | ||||||
Annual ten fastest men 200 km | Polynomial | 0.36 | 0 | -6.75 | Linear | Undetermined | 0.27 | 0.46 | 53.4% |
Linear | 1.12 | 4 | -7.02 | ||||||
Annual ten fastest women 1,000 km | Polynomial | 1.32 e-20 | 0 | -136.61 | Polynomial | Undetermined | 135.24 | 4.27 e-30 | 100% |
Linear | 0.25 | 1 | -1.36 |