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 + 13
This means that on average for every extra kilogram weight a rider loses 0.2 positions in the result.
Miller
3
72 kgDavis
4
60 kgZucconi
10
63 kgCappelle
11
71 kgGuyton
17
74 kgDavis
20
73 kgTashiro
22
54 kgFukushima
23
62 kgMiura
26
67 kgSuzuki
27
60 kgAbe
30
67 kgCalcagni
33
65 kgMiyazawa
38
61 kgLupeikis
40
80 kgGerrans
48
62 kgApollonio
54
70 kgBrown
56
76 kgReid
61
62 kg
3
72 kgDavis
4
60 kgZucconi
10
63 kgCappelle
11
71 kgGuyton
17
74 kgDavis
20
73 kgTashiro
22
54 kgFukushima
23
62 kgMiura
26
67 kgSuzuki
27
60 kgAbe
30
67 kgCalcagni
33
65 kgMiyazawa
38
61 kgLupeikis
40
80 kgGerrans
48
62 kgApollonio
54
70 kgBrown
56
76 kgReid
61
62 kg
Weight (KG) →
Result →
80
54
3
61
| # | Rider | Weight (KG) |
|---|---|---|
| 3 | MILLER Graeme | 72 |
| 4 | DAVIS Scott | 60 |
| 10 | ZUCCONI Pietro | 63 |
| 11 | CAPPELLE Andy | 71 |
| 17 | GUYTON Scott | 74 |
| 20 | DAVIS Allan | 73 |
| 22 | TASHIRO Yasutaka | 54 |
| 23 | FUKUSHIMA Shinichi | 62 |
| 26 | MIURA Kyoshi | 67 |
| 27 | SUZUKI Shinri | 60 |
| 30 | ABE Yoshiyuki | 67 |
| 33 | CALCAGNI Patrick | 65 |
| 38 | MIYAZAWA Takashi | 61 |
| 40 | LUPEIKIS Remigius | 80 |
| 48 | GERRANS Simon | 62 |
| 54 | APOLLONIO Massimo | 70 |
| 56 | BROWN Graeme Allen | 76 |
| 61 | REID Robin | 62 |