Diferentes Tipos De Planes En Un Inventario

ÉSTRADA ANDRES MONSERRAT

VEGA OLVERA JUAN CARLOS

ING INDUSTRIAL 4B

EJERCICIO REGRESION SIMPLE.

En un estudio realizado por el seguro social se pretende saber que tanto depende el peso respecto a la estatura ya que las personas toman como pretexto la estatura para decir que están con sobre peso u obesos, para esto se tiene los siguientes datos.

ESTATURA (cm) - x PESO (kg) - y

170 63

155 50

168 65

152 59

173 53

170 52

164 80

158 52

165 65

170 73

170 73

185 95

170 58

172 72

177 185

180 73

170 95

172 65

180 70

176 62

178 70

180 125

169 85

165 62

165 74

183 87

160 50

159 60

170 90

175 71

172 75

170 63

176 90

160 49

168 66

169 70

170 60

163 49

164 70

153 54

155 49

155 67

168 59

FORMULAS

PESO (Y) ESTATURA (X)

63 170 1.53488372 -8.046512 -12.3504597 2.355868037

50 155 -13.465116 -21.04651 283.393726 181.3093564

65 168 -0.4651163 -6.046512 2.81233099 0.216333153

59 152 -16.465116 -12.04651 198.347215 271.1000541

53 173 4.53488372 -18.04651 -81.8388318 20.56517036

52 170 1.53488372 -19.04651 -29.2341806 2.355868037

80 164 -4.4651163 8.9534884 -39.9783667 19.93726339

52 158 -10.465116 -19.04651 199.323959 109.5186587

65 165 -3.4651163 -6.046512 20.9518659 12.00703083

73 170 1.53488372 1.9534884 2.9983775 2.355868037

73 170 1.53488372 1.9534884 2.9983775 2.355868037

95 185 16.5348837 23.953488 396.068145 273.4023797

58 170 1.53488372 -13.04651 -20.0248783 2.355868037

72 172 3.53488372 0.9534884 3.37047052 12.49540292

185 177 8.53488372 113.95349 972.579773 72.84424013

73 180 11.5348837 1.9534884 22.5332612 133.0535425

95 170 1.53488372 23.953488 36.7658194 2.355868037

65 172 3.53488372 -6.046512 -21.3737155 12.49540292

70 180 11.5348837 -1.046512 -12.0713899 133.0535425

62 176 7.53488372 -9.046512 -68.1644132 56.77447269

70 178 9.53488372 -1.046512 -9.97836668 90.91400757

125 180 11.5348837 53.953488 622.347215 133.0535425

85 169 0.53488372 13.953488 7.46349378 0.286100595

62 165 -3.4651163 -9.046512 31.3472147 12.00703083

74 165 -3.4651163 2.9534884 -10.2341806 12.00703083

87 183 14.5348837 15.953488 231.882098 211.2628448

50 160 -8.4651163 -21.04651 178.161168 71.65819362

60 159 -9.4651163 -11.04651 104.556517 89.58842618

90 170 1.53488372 18.953488 29.0914008 2.355868037

71 175 6.53488372 -0.046512 -0.30394808 42.70470525

75 172 3.53488372 3.9534884 13.9751217 12.49540292

63 170 1.53488372 -8.046512 -12.3504597 2.355868037

90 176 7.53488372 18.953488 142.812331 56.77447269

49 160 -8.4651163 -22.04651 186.626284 71.65819362

66 168 -0.4651163 -5.046512 2.34721471 0.216333153

70 169 0.53488372 -1.046512 -0.55976203 0.286100595

60 170 1.53488372 -11.04651 -16.9551109 2.355868037

49 163 -5.4651163 -22.04651 120.48675 29.86749594

70 164 -4.4651163 -1.046512 4.67279611 19.93726339

54 153 -15.465116 -17.04651 263.626284 239.1698215

49 155 -13.465116 -22.04651 296.858843 181.3093564

67 155 -13.465116 -4.046512 54.4867496 181.3093564

59 168 -0.4651163 -12.04651 5.60302866 0.216333153

PROMEDIO PROMEDIO

71.04651163 168.4651163 -3.411E-13 -1.56E-13 4103.06977 2786.697674

β= 1.472377074

α=ȳ-βẋ -176.9976633

Encontremos los valores de

Quedando la ecuación de estimación:

ŷ

ŷ - ȳ (ŷ - ȳ)^2

167.040067 2.9599325 8.76120067 2.35586804 -1.42505 2.0307642

164.737749 -9.737749 94.8237496 181.309356 -3.72737 13.893269

167.39427 0.6057297 0.36690842 0.21633315 -1.07085 1.146711

166.331662 -14.33166 205.396527 271.100054 -2.13345 4.5516285

165.269053 7.730947 59.7675412 20.5651704 -3.19606 10.21482

165.091952 4.9080484 24.0889393 2.35586804 -3.37316 11.37824

170.050792 -6.050792 36.6120838 19.9372634 1.585676 2.5143675

165.091952 -7.091952 50.2957772 109.518659 -3.37316 11.37824

167.39427 -2.39427 5.73253047 12.0070308 -1.07085 1.146711

168.811082 1.1889181 1.41352627 2.35586804 0.345966 0.1196922

168.811082 1.1889181 1.41352627 2.35586804 0.345966 0.1196922

172.707314 12.292686 151.110138 273.40238 4.242197 17.996238

166.15456 3.8454398 14.787407 2.35586804 -2.31056 5.3386692

168.63398 3.3660196 11.3300876 12.4954029 0.168864 0.0285151

188.646444 -11.64644 135.639648 72.8442401 20.18133 407.28597

168.811082 11.188918 125.191888 133.053542 0.345966 0.1196922

172.707314 -2.707314 7.32954718 2.35586804 4.242197 17.996238

167.39427 4.6057297 21.2127457 12.4954029 -1.07085 1.146711

168.279778 11.720222 137.363614 133.053542 -0.18534 0.0343504

166.862966 9.137034 83.4853901 56.7744727 -1.60215 2.5668855

168.279778 9.7202224 94.4827243 90.9140076 -0.18534 0.0343504

178.020357 1.9796431 3.91898661 133.053542 9.555241 91.302624

170.936299 -1.936299 3.74925463 0.28610059 2.471183 6.1067451

166.862966 -1.862966 3.47064236 12.0070308 -1.60215 2.5668855

168.988183 -3.988183 15.9056063 12.0070308 0.523067 0.2735991

171.290502 11.709498 137.112341 211.262845 2.825386 7.982805

164.737749 -4.737749 22.4462627 71.6581936 -3.72737 13.893269

166.508763 -7.508763 56.3815237 89.5884262 -1.95635 3.8273177

171.821806 -1.821806 3.31897866 2.35586804 3.35669 11.267369

168.456879 6.543121 42.8124324 42.7047052 -0.00824 6.785E-05

169.165285 2.8347152 8.0356104 12.4954029 0.700168 0.4902359

167.040067 2.9599325 8.76120067 2.35586804 -1.42505 2.0307642

171.821806 4.1781936 17.4573015 56.7744727 3.35669 11.267369

164.560647 -4.560647 20.7995033 71.6581936 -3.90447 15.244878

167.571372 0.4286282 0.18372215 0.21633315 -0.89374 0.7987792

168.279778 0.7202224 0.51872036 0.28610059 -0.18534 0.0343504

...