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 = -1.4 * weight + 138
This means that on average for every extra kilogram weight a rider loses -1.4 positions in the result.
Sweet
1
69 kgMitchell
2
70 kgHayles
5
80 kgAndersen
7
71 kgTanner
10
70 kgGrabsch
19
81 kgde Groot
22
65 kgNewton
37
69 kgGeorge
46
61 kgGono
47
69 kgGreen
48
75 kgWohlberg
49
63 kgCalcagni
62
65 kgWhite
63
72 kgTang
64
71 kgEspiritu
67
56 kgValach
70
75 kgDvorščík
74
68 kgLandry
76
77 kgFujita
86
58 kg
1
69 kgMitchell
2
70 kgHayles
5
80 kgAndersen
7
71 kgTanner
10
70 kgGrabsch
19
81 kgde Groot
22
65 kgNewton
37
69 kgGeorge
46
61 kgGono
47
69 kgGreen
48
75 kgWohlberg
49
63 kgCalcagni
62
65 kgWhite
63
72 kgTang
64
71 kgEspiritu
67
56 kgValach
70
75 kgDvorščík
74
68 kgLandry
76
77 kgFujita
86
58 kg
Weight (KG) →
Result →
81
56
1
86
| # | Rider | Weight (KG) |
|---|---|---|
| 1 | SWEET Jay | 69 |
| 2 | MITCHELL Glen | 70 |
| 5 | HAYLES Robert | 80 |
| 7 | ANDERSEN Christian | 71 |
| 10 | TANNER John | 70 |
| 19 | GRABSCH Ralf | 81 |
| 22 | DE GROOT Bram | 65 |
| 37 | NEWTON Christopher | 69 |
| 46 | GEORGE David | 61 |
| 47 | GONO Marcel | 69 |
| 48 | GREEN Roland | 75 |
| 49 | WOHLBERG Eric | 63 |
| 62 | CALCAGNI Patrick | 65 |
| 63 | WHITE Matthew | 72 |
| 64 | TANG Xuezhong | 71 |
| 67 | ESPIRITU Victor | 56 |
| 70 | VALACH Ján | 75 |
| 74 | DVORŠČÍK Milan | 68 |
| 76 | LANDRY Jacques | 77 |
| 86 | FUJITA Kozo | 58 |