Regression line on weight and result
With regression analysis we can check if there is a relationship between a dependent (also called outcome variable) and an independent variable. In this statistic, the relationship between the weight of a rider and the result (outcome) is investigated.
The formula for the regression line on the riders in the result is as follows:
The formula for the regression line on the riders in the result is as follows:
result = -0.1 * weight + 20
This means that on average for every extra kilogram weight a rider loses -0.1 positions in the result.
Deignan
1
57 kgHosking
2
60 kgOlds
3
54 kgBrand
5
57 kgvan Dijk
6
71 kgBronzini
8
54 kgJohansson
9
58 kgD'hoore
10
63 kgJeuland-Tranchant
12
61 kgLongo Borghini
13
59 kgKitchen
14
60 kgScandolara
17
52 kgConfalonieri
18
56 kgPieters
20
58 kgDruyts
21
62 kgGuarischi
22
57 kg
1
57 kgHosking
2
60 kgOlds
3
54 kgBrand
5
57 kgvan Dijk
6
71 kgBronzini
8
54 kgJohansson
9
58 kgD'hoore
10
63 kgJeuland-Tranchant
12
61 kgLongo Borghini
13
59 kgKitchen
14
60 kgScandolara
17
52 kgConfalonieri
18
56 kgPieters
20
58 kgDruyts
21
62 kgGuarischi
22
57 kg
Weight (KG) →
Result →
71
52
1
22
| # | Rider | Weight (KG) |
|---|---|---|
| 1 | DEIGNAN Elizabeth | 57 |
| 2 | HOSKING Chloe | 60 |
| 3 | OLDS Shelley | 54 |
| 5 | BRAND Lucinda | 57 |
| 6 | VAN DIJK Ellen | 71 |
| 8 | BRONZINI Giorgia | 54 |
| 9 | JOHANSSON Emma | 58 |
| 10 | D'HOORE Jolien | 63 |
| 12 | JEULAND-TRANCHANT Pascale | 61 |
| 13 | LONGO BORGHINI Elisa | 59 |
| 14 | KITCHEN Lauren | 60 |
| 17 | SCANDOLARA Valentina | 52 |
| 18 | CONFALONIERI Maria Giulia | 56 |
| 20 | PIETERS Amy | 58 |
| 21 | DRUYTS Kelly | 62 |
| 22 | GUARISCHI Barbara | 57 |