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 = 0.1 * weight + 9
This means that on average for every extra kilogram weight a rider loses 0.1 positions in the result.
Viviani
1
67 kgKristoff
2
78 kgvan Poppel
3
82 kgEwan
4
69 kgGuardini
5
66 kgAckermann
6
78 kgTrusov
7
77 kgAlbanese
8
70 kgSkujiņš
9
70 kgHalvorsen
10
69 kgValverde
11
61 kgTonelli
12
64 kgBonifazio
13
72 kgMcLay
14
72 kgRenshaw
15
74 kgBauhaus
16
75 kgPorsev
17
80 kgBarbier
18
79 kgCaruso
19
67 kgRojas
21
70 kgPlanet
22
71 kgGreipel
23
80 kgDennis
24
72 kgVenter
25
70 kg
1
67 kgKristoff
2
78 kgvan Poppel
3
82 kgEwan
4
69 kgGuardini
5
66 kgAckermann
6
78 kgTrusov
7
77 kgAlbanese
8
70 kgSkujiņš
9
70 kgHalvorsen
10
69 kgValverde
11
61 kgTonelli
12
64 kgBonifazio
13
72 kgMcLay
14
72 kgRenshaw
15
74 kgBauhaus
16
75 kgPorsev
17
80 kgBarbier
18
79 kgCaruso
19
67 kgRojas
21
70 kgPlanet
22
71 kgGreipel
23
80 kgDennis
24
72 kgVenter
25
70 kg
Weight (KG) →
Result →
82
61
1
25
# | Rider | Weight (KG) |
---|---|---|
1 | VIVIANI Elia | 67 |
2 | KRISTOFF Alexander | 78 |
3 | VAN POPPEL Danny | 82 |
4 | EWAN Caleb | 69 |
5 | GUARDINI Andrea | 66 |
6 | ACKERMANN Pascal | 78 |
7 | TRUSOV Nikolay | 77 |
8 | ALBANESE Vincenzo | 70 |
9 | SKUJIŅŠ Toms | 70 |
10 | HALVORSEN Kristoffer | 69 |
11 | VALVERDE Alejandro | 61 |
12 | TONELLI Alessandro | 64 |
13 | BONIFAZIO Niccolò | 72 |
14 | MCLAY Daniel | 72 |
15 | RENSHAW Mark | 74 |
16 | BAUHAUS Phil | 75 |
17 | PORSEV Alexander | 80 |
18 | BARBIER Rudy | 79 |
19 | CARUSO Damiano | 67 |
21 | ROJAS José Joaquín | 70 |
22 | PLANET Charles | 71 |
23 | GREIPEL André | 80 |
24 | DENNIS Rohan | 72 |
25 | VENTER Jaco | 70 |