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 - 2
This means that on average for every extra kilogram weight a rider loses 0.2 positions in the result.
Valverde
1
61 kgHushovd
2
83 kgLeipheimer
3
62 kgEvans
4
64 kgSchröder
5
64 kgWegmann
6
60 kgMonfort
7
66 kgEfimkin
8
67 kgZubeldia
9
68 kgLancaster
10
78 kgVoeckler
11
71 kgQuinziato
12
74 kgBarredo
13
61 kgVelits
14
63 kgAgnoli
15
72 kgLewis
16
65 kgBak
17
76 kgGrabovskyy
18
69 kgGreipel
19
80 kgGadret
20
58 kgIsasi
21
70 kgHansen
22
72 kgAstarloza
23
72 kgLópez
24
68 kg
1
61 kgHushovd
2
83 kgLeipheimer
3
62 kgEvans
4
64 kgSchröder
5
64 kgWegmann
6
60 kgMonfort
7
66 kgEfimkin
8
67 kgZubeldia
9
68 kgLancaster
10
78 kgVoeckler
11
71 kgQuinziato
12
74 kgBarredo
13
61 kgVelits
14
63 kgAgnoli
15
72 kgLewis
16
65 kgBak
17
76 kgGrabovskyy
18
69 kgGreipel
19
80 kgGadret
20
58 kgIsasi
21
70 kgHansen
22
72 kgAstarloza
23
72 kgLópez
24
68 kg
Weight (KG) →
Result →
83
58
1
24
# | Rider | Weight (KG) |
---|---|---|
1 | VALVERDE Alejandro | 61 |
2 | HUSHOVD Thor | 83 |
3 | LEIPHEIMER Levi | 62 |
4 | EVANS Cadel | 64 |
5 | SCHRÖDER Björn | 64 |
6 | WEGMANN Fabian | 60 |
7 | MONFORT Maxime | 66 |
8 | EFIMKIN Vladimir | 67 |
9 | ZUBELDIA Haimar | 68 |
10 | LANCASTER Brett | 78 |
11 | VOECKLER Thomas | 71 |
12 | QUINZIATO Manuel | 74 |
13 | BARREDO Carlos | 61 |
14 | VELITS Peter | 63 |
15 | AGNOLI Valerio | 72 |
16 | LEWIS Craig | 65 |
17 | BAK Lars Ytting | 76 |
18 | GRABOVSKYY Dmytro | 69 |
19 | GREIPEL André | 80 |
20 | GADRET John | 58 |
21 | ISASI Iñaki | 70 |
22 | HANSEN Adam | 72 |
23 | ASTARLOZA Mikel | 72 |
24 | LÓPEZ David | 68 |