Jury Statistics
| Jury | <G> | σG | σG-P | <G-P> | nG | nSF | nT | κ |
|---|---|---|---|---|---|---|---|---|
| Гладышкина А.В. | 13.4 | 5.93 | 1.87 | 0.1 | 27 | 3 | 7 | 0.45 |
| Хвалюк А.В. | 12.4 | 5.29 | 1.92 | 0.66 | 27 | 3 | 6 | 0.21 |
| Пислярук А.К. | 12.4 | 6.17 | 1.65 | 0.56 | 45 | 5 | 9 | 1.11 |
| Левашева А.С. | 12.2 | 5.25 | 1.33 | 0.13 | 45 | 5 | 8 | 0.28 |
| Невенченко А.С. | 12.0 | 5.13 | 1.52 | -0.14 | 45 | 5 | 9 | 0.22 |
| Червинская А.С. | 12.2 | 5.33 | 1.49 | -0.17 | 45 | 5 | 7 | 0.33 |
| Зигаёв В.А. | 13.2 | 5.91 | 2.06 | 0.61 | 45 | 5 | 8 | 0.52 |
| Гридяев В.Е. | 10.2 | 4.19 | 1.92 | -1.4 | 45 | 5 | 8 | 0.04 |
| Ерёмин В.С. | 16.2 | 7.26 | 2.51 | 2.59 | 27 | 3 | 7 | 0.64 |
| Матыцин В.С. | 11.1 | 5.04 | 1.38 | -1.11 | 18 | 2 | 4 | 0.51 |
| Андреищева Д.В. | 11.1 | 5.07 | 1.42 | -0.39 | 45 | 5 | 6 | 0.54 |
| Крохина Е.В. | 12.3 | 5.51 | 1.76 | -0.72 | 18 | 2 | 4 | 0.47 |
| Юносов Е.Н. | 19.0 | 8.38 | 1.49 | 2.28 | 9 | 1 | 3 | 0.62 |
| Марченко И.А. | 11.1 | 5.28 | 2.31 | -0.83 | 45 | 5 | 8 | 0.74 |
| Абашкина И.В. | 11.6 | 4.97 | 1.25 | -0.04 | 27 | 3 | 6 | 0.24 |
| Беляева И.В. | 14.6 | 6.34 | 1.9 | 0.8 | 18 | 2 | 5 | 0.38 |
| Шикова И.В. | 12.3 | 5.73 | 1.4 | 0.5 | 45 | 5 | 7 | 0.69 |
| Никитков К.А, | 14.1 | 5.51 | 1.23 | 1.05 | 18 | 2 | 5 | -0.25 |
| Свешникова Л.В. | 10.4 | 4.2 | 2.63 | -1.47 | 27 | 3 | 6 | -0.03 |
| Селиверстова Н.В. | 13.4 | 5.07 | 1.28 | 0.66 | 27 | 3 | 5 | -0.42 |
| Чиляева Н.М. | 11.4 | 4.53 | 1.62 | -0.22 | 36 | 4 | 6 | -0.1 |
| Рыбкина П.Ю. | 11.5 | 5.46 | 1.75 | -0.99 | 45 | 5 | 7 | 0.78 |
| Козелков С.И. | 12.6 | 6.41 | 0.85 | -0.09 | 45 | 5 | 8 | 1.25 |
| Горожанина Т.А. | 12.2 | 4.61 | 1.13 | -0.02 | 9 | 1 | 3 | -0.38 |
| Ачкасова Т.В. | 12.4 | 6.69 | 1.52 | -0.52 | 27 | 3 | 6 | 1.64 |
| Панина Т.Н. | 14.4 | 6.99 | 1.99 | -2.28 | 9 | 1 | 3 | 1.1 |
| Байбакова Ю.А. | 14.6 | 6.49 | 1.47 | 0.84 | 45 | 5 | 7 | 0.55 |
How we calculate this statistics?
This table presents statistical analysis of jury grading behavior across multiple Science Fights. Each row corresponds to a single jury member. κ = σG − 0.40825 × <G>. <G> is the mean grade, σG the standard deviation of grades, σG-P the standard deviation of residuals (grade minus performance), <G-P> the mean residual, nG the number of grades, nSF the number of Science Fights judged, and nT the number of unique teams judged.