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 + 31
This means that on average for every extra kilogram weight a rider loses 0.2 positions in the result.
Haedo
2
73 kgDomínguez
3
72 kgHorner
5
70 kgMitchell
22
70 kgFrischkorn
26
68 kgSuzuki
28
60 kgKilleen
31
65 kgWohlberg
33
63 kgVan den Broeck
35
69 kgPate
51
73 kgDuggan
55
60 kgFrattini
58
63 kgAbe
62
67 kgLewis
64
65 kgMcCarty
77
68 kgHenderson
96
75 kgFraser
105
71 kg
2
73 kgDomínguez
3
72 kgHorner
5
70 kgMitchell
22
70 kgFrischkorn
26
68 kgSuzuki
28
60 kgKilleen
31
65 kgWohlberg
33
63 kgVan den Broeck
35
69 kgPate
51
73 kgDuggan
55
60 kgFrattini
58
63 kgAbe
62
67 kgLewis
64
65 kgMcCarty
77
68 kgHenderson
96
75 kgFraser
105
71 kg
Weight (KG) →
Result →
75
60
2
105
| # | Rider | Weight (KG) |
|---|---|---|
| 2 | HAEDO Juan José | 73 |
| 3 | DOMÍNGUEZ Iván | 72 |
| 5 | HORNER Chris | 70 |
| 22 | MITCHELL Glen | 70 |
| 26 | FRISCHKORN William | 68 |
| 28 | SUZUKI Shinri | 60 |
| 31 | KILLEEN Liam | 65 |
| 33 | WOHLBERG Eric | 63 |
| 35 | VAN DEN BROECK Jurgen | 69 |
| 51 | PATE Danny | 73 |
| 55 | DUGGAN Timothy | 60 |
| 58 | FRATTINI Davide | 63 |
| 62 | ABE Yoshiyuki | 67 |
| 64 | LEWIS Craig | 65 |
| 77 | MCCARTY Jonathan Patrick | 68 |
| 96 | HENDERSON Gregory | 75 |
| 105 | FRASER Gordon | 71 |