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 = -0.4 * weight + 33
This means that on average for every extra kilogram weight a rider loses -0.4 positions in the result.
Tanner
1
70 kgHayles
1
80 kgNewton
1
69 kgSweet
2
69 kgGates
2
71 kgAndersen
3
71 kgGeorge
4
61 kgGono
5
69 kgWhite
5
72 kgDvorščík
6
68 kgLipták
6
68 kgValach
6
75 kgCalcagni
8
65 kgMitchell
9
70 kgGreen
10
75 kgLandry
10
77 kgWohlberg
10
63 kgGrabsch
11
81 kgFujita
16
58 kgSuzuki
16
60 kgEspiritu
17
56 kgde Groot
18
65 kgTang
19
71 kg
1
70 kgHayles
1
80 kgNewton
1
69 kgSweet
2
69 kgGates
2
71 kgAndersen
3
71 kgGeorge
4
61 kgGono
5
69 kgWhite
5
72 kgDvorščík
6
68 kgLipták
6
68 kgValach
6
75 kgCalcagni
8
65 kgMitchell
9
70 kgGreen
10
75 kgLandry
10
77 kgWohlberg
10
63 kgGrabsch
11
81 kgFujita
16
58 kgSuzuki
16
60 kgEspiritu
17
56 kgde Groot
18
65 kgTang
19
71 kg
Weight (KG) →
Result →
81
56
1
19
| # | Rider | Weight (KG) |
|---|---|---|
| 1 | TANNER John | 70 |
| 1 | HAYLES Robert | 80 |
| 1 | NEWTON Christopher | 69 |
| 2 | SWEET Jay | 69 |
| 2 | GATES Nick | 71 |
| 3 | ANDERSEN Christian | 71 |
| 4 | GEORGE David | 61 |
| 5 | GONO Marcel | 69 |
| 5 | WHITE Matthew | 72 |
| 6 | DVORŠČÍK Milan | 68 |
| 6 | LIPTÁK Miroslav | 68 |
| 6 | VALACH Ján | 75 |
| 8 | CALCAGNI Patrick | 65 |
| 9 | MITCHELL Glen | 70 |
| 10 | GREEN Roland | 75 |
| 10 | LANDRY Jacques | 77 |
| 10 | WOHLBERG Eric | 63 |
| 11 | GRABSCH Ralf | 81 |
| 16 | FUJITA Kozo | 58 |
| 16 | SUZUKI Shinri | 60 |
| 17 | ESPIRITU Victor | 56 |
| 18 | DE GROOT Bram | 65 |
| 19 | TANG Xuezhong | 71 |