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 + 57
This means that on average for every extra kilogram weight a rider loses -0.2 positions in the result.
van Dijk
2
71 kgVigié
6
58 kgGuarischi
8
57 kgFidanza
10
60 kgBarbieri
12
55 kgLach
17
59 kgMagner
22
57 kgConsonni
24
59 kgAchtereekte
26
60 kgvan der Hulst
29
66 kgCopponi
31
55 kgBeuling
37
65 kgKuijpers
42
73 kgDe Wilde
43
62 kgMartins
52
61 kgGreenwood
56
60 kgVitillo
59
51 kgTacey
63
62 kgFortin
66
55 kgStern
68
55 kgStultiens
69
58 kgBolks
73
60 kgSels
87
65 kgTeutenberg
94
53 kgLópez
108
67 kg
2
71 kgVigié
6
58 kgGuarischi
8
57 kgFidanza
10
60 kgBarbieri
12
55 kgLach
17
59 kgMagner
22
57 kgConsonni
24
59 kgAchtereekte
26
60 kgvan der Hulst
29
66 kgCopponi
31
55 kgBeuling
37
65 kgKuijpers
42
73 kgDe Wilde
43
62 kgMartins
52
61 kgGreenwood
56
60 kgVitillo
59
51 kgTacey
63
62 kgFortin
66
55 kgStern
68
55 kgStultiens
69
58 kgBolks
73
60 kgSels
87
65 kgTeutenberg
94
53 kgLópez
108
67 kg
Weight (KG) →
Result →
73
51
2
108
# | Rider | Weight (KG) |
---|---|---|
2 | VAN DIJK Ellen | 71 |
6 | VIGIÉ Margaux | 58 |
8 | GUARISCHI Barbara | 57 |
10 | FIDANZA Martina | 60 |
12 | BARBIERI Rachele | 55 |
17 | LACH Marta | 59 |
22 | MAGNER Alexis | 57 |
24 | CONSONNI Chiara | 59 |
26 | ACHTEREEKTE Carlijn | 60 |
29 | VAN DER HULST Amber | 66 |
31 | COPPONI Clara | 55 |
37 | BEULING Femke | 65 |
42 | KUIJPERS Evy | 73 |
43 | DE WILDE Julie | 62 |
52 | MARTINS Maria | 61 |
56 | GREENWOOD Monica | 60 |
59 | VITILLO Matilde | 51 |
63 | TACEY April | 62 |
66 | FORTIN Valentine | 55 |
68 | STERN Léa | 55 |
69 | STULTIENS Sabrina | 58 |
73 | BOLKS Florien | 60 |
87 | SELS Loes | 65 |
94 | TEUTENBERG Lea Lin | 53 |
108 | LÓPEZ Marga | 67 |