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 + 34
This means that on average for every extra kilogram weight a rider loses -0.1 positions in the result.
Soeder
1
52 kgDoppmann
4
55 kgCarrigan
5
60 kgLjungskog
6
57 kgBecker
7
64 kgArndt
8
59 kgSpratt
12
55 kgPitel
14
52 kgValen
18
62 kgCantele
23
58 kgSlappendel
25
67 kgWood
30
56 kgGuderzo
31
54 kgKiesanowski
38
56 kgMeng
41
65 kgGilmore
49
56 kgHohl
60
55 kgSchleicher
64
58 kgMin
69
56 kg
1
52 kgDoppmann
4
55 kgCarrigan
5
60 kgLjungskog
6
57 kgBecker
7
64 kgArndt
8
59 kgSpratt
12
55 kgPitel
14
52 kgValen
18
62 kgCantele
23
58 kgSlappendel
25
67 kgWood
30
56 kgGuderzo
31
54 kgKiesanowski
38
56 kgMeng
41
65 kgGilmore
49
56 kgHohl
60
55 kgSchleicher
64
58 kgMin
69
56 kg
Weight (KG) →
Result →
67
52
1
69
| # | Rider | Weight (KG) |
|---|---|---|
| 1 | SOEDER Christiane | 52 |
| 4 | DOPPMANN Priska | 55 |
| 5 | CARRIGAN Sara | 60 |
| 6 | LJUNGSKOG Susanne | 57 |
| 7 | BECKER Charlotte | 64 |
| 8 | ARNDT Judith | 59 |
| 12 | SPRATT Amanda | 55 |
| 14 | PITEL Edwige | 52 |
| 18 | VALEN Anita | 62 |
| 23 | CANTELE Noemi | 58 |
| 25 | SLAPPENDEL Iris | 67 |
| 30 | WOOD Oenone | 56 |
| 31 | GUDERZO Tatiana | 54 |
| 38 | KIESANOWSKI Joanne | 56 |
| 41 | MENG Lang | 65 |
| 49 | GILMORE Rochelle | 56 |
| 60 | HOHL Jennifer | 55 |
| 64 | SCHLEICHER Regina | 58 |
| 69 | MIN Gao | 56 |