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 = -0.2 * weight + 28
This means that on average for every extra kilogram weight a rider loses -0.2 positions in the result.
Zberg
1
72 kgCancellara
2
80 kgLoosli
3
71 kgAlbasini
4
65 kgCalcagni
7
65 kgStalder
8
58 kgMorabito
9
74 kgElmiger
10
73 kgZberg
11
69 kgRast
12
80 kgDietziker
13
67 kgAckermann
14
62 kgSchär
15
78 kgZampieri
16
62 kgTschopp
17
62 kgBertogliati
18
73 kgBourgeois
21
61 kg
1
72 kgCancellara
2
80 kgLoosli
3
71 kgAlbasini
4
65 kgCalcagni
7
65 kgStalder
8
58 kgMorabito
9
74 kgElmiger
10
73 kgZberg
11
69 kgRast
12
80 kgDietziker
13
67 kgAckermann
14
62 kgSchär
15
78 kgZampieri
16
62 kgTschopp
17
62 kgBertogliati
18
73 kgBourgeois
21
61 kg
Weight (KG) →
Result →
80
58
1
21
| # | Rider | Weight (KG) |
|---|---|---|
| 1 | ZBERG Beat | 72 |
| 2 | CANCELLARA Fabian | 80 |
| 3 | LOOSLI David | 71 |
| 4 | ALBASINI Michael | 65 |
| 7 | CALCAGNI Patrick | 65 |
| 8 | STALDER Florian | 58 |
| 9 | MORABITO Steve | 74 |
| 10 | ELMIGER Martin | 73 |
| 11 | ZBERG Markus | 69 |
| 12 | RAST Grégory | 80 |
| 13 | DIETZIKER Andreas | 67 |
| 14 | ACKERMANN Silvère | 62 |
| 15 | SCHÄR Michael | 78 |
| 16 | ZAMPIERI Steve | 62 |
| 17 | TSCHOPP Johann | 62 |
| 18 | BERTOGLIATI Rubens | 73 |
| 21 | BOURGEOIS Guillaume | 61 |