Aproximación Funcional Regresión Lineal 1 Organizada
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K Presión EDAD 1 144 39 2 220 47 3 138 45 4 145 47 5 162 65 6 142 46 7 170 67 8 124 42 9 158 67 10 154 56 11 162 64 12 150 56 13 140 59 14 110 34 15 128 42 16 130 48 17 135 45 18 114 17 19 116 20 Suma(XiYi) 20 124 19 5616 199576 21 136 36 10340 22 142 50 6210 23 120 39 6815 24 120 21 10530 25 160 44 6532 26 158 53 11390 27 144 63 5208 28 130 29 10586 29 125 25 8624 30 175 69 10368 8400 8260 3740 5376 B1= 0.97087035 6240 6075 B0= 98.7147181 1938 2320 Y= B0+B1X 2356 Y= 98,71+0,97X 4896 7100 4680 2520 7040 10 20 30 40 0 50 100 150 200 250 Dat
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Transcript of Aproximación Funcional Regresión Lineal 1 Organizada
K Presión EDAD1 144 392 220 473 138 454 145 475 162 656 142 467 170 678 124 429 158 67
10 154 5611 162 6412 150 5613 140 5914 110 3415 128 4216 130 4817 135 4518 114 1719 116 20 Suma(XiYi)20 124 19 5616 19957621 136 36 1034022 142 50 621023 120 39 681524 120 21 1053025 160 44 653226 158 53 1139027 144 63 520828 130 29 1058629 125 25 862430 175 69 10368
8400826037405376
B1= 0.97087035 62406075
B0= 98.7147181 19382320
Y= B0+B1X 2356Y= 98,71+0,97X 4896
7100468025207040837490723770
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312512075
Suma(Xi^2) Suma(Xi)^2 SUMA(Xi) SUMA(Yi)1521 67894 1833316 1354 42762209202522094225211644891764448931364096313634811156176423042025
289400361
129625001521
441193628093969
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6254761
x y1 1 1 1842 1.2 2.43 1.8 5.44 2.5 105 3.6 186 4.7 28.27 6.6 46.28 9.1 72.8
B1 1.1130952381
B0 -1.1964285714SSE
y Bo+B1XY -1,19+1,11x
REGRESION LINEAL coeficiente de correlacionY ESTIMADO ERROR e^2 y^2-0.0833333333 1.0833333333 1.17361111 11.02976190476 0.1702380952 0.02898101 1.442.14285714286 -0.342857143 0.11755102 3.243.25595238095 -0.755952381 0.571464 6.254.36904761905 -0.769047619 0.59143424 12.965.48214285714 -0.782142857 0.61174745 22.096.59523809524 0.0047619048 2.26757E-05 43.567.70833333333 1.3916666667 1.93673611 82.81
tabla ANOVAfuente grado libert SS MS FRregresion x 1 52.037202381 52.0372024 62.0531172364841residual 6 5.031547619 0.83859127total 7 57.06875
SSY 7.91015625 57.068756.825156254.050156251.722656250.045156250.787656257.77015625
27.95765625
SSE 1.17361111111 5.0315476190.028981009070.117551020410.571464002270.591434240360.611747448982.2675737E-051.93673611111
SSY-SSE 15.1775173611 52.0372023817.743631306692.787707270410.309745252270.309745252272.787707270417.7436313066915.1775173611
x^2 suma(x^2) suma(X)^21 204 129649
1625364964
5.03154761904762
analisis de varianzaYestimado-Ymedia y promedio (y stimado-y mdia)^2
-3.89583333333333 15.1775174-2.7827380952381 3.8125 7.74363131
-1.66964285714286 2.78770727-0.556547619047619 0.30974525
0.55654761904762 0.309745251.66964285714286 2.78770727
2.7827380952381 7.743631313.89583333333333 15.1775174
EMS
NC 99.90%ALFA 0.10%F CRITICA 35.507490253
r^2 0.9118335758
0 1 2 3 4 5 6 7 8 90
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suma(x) suma(y)36 30.5
0 1 2 3 4 5 6 7 8 90
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DATOSi y x Grado 2individuo gana pero dosis x^2 x^3 x^4 xy
1 1 1 1 1 1 12 1.2 2 4 8 16 2.43 1.8 3 9 27 81 5.44 2.5 4 16 64 256 105 3.6 5 25 125 625 186 4.7 6 36 216 1296 28.27 6.6 7 49 343 2401 46.28 9.1 8 64 512 4096 72.8
total 30.5 36 204 1296 8772 184
MATRIZ 8 36 204 a1 30.536 204 1296 a2 184
204 1296 8772 a3 1227
inversa 1.94642857 -0.91071429 0.08928571-0.91071429 0.50595238 -0.053571430.08928571 -0.05357143 0.00595238
AO 1.348 1.34-0,41x+0,17A1 -0.414A2 0.170
ANALISI DE VARIANZA ANOVA
FUENTE GL SS MS F(calculado)REGRESION 2 56.87 28.4360119 722.73RESIDUAL 5 0.20 0.03934524TOTAL 7 57.07 Fcritico 5.78613504
alfa 0.05
FUENTE GL SS MS F(calculado)
REGRESION11
RESIDUAL 5TOTAL 7
x^2.y y estimado e= y-yEstimado e^2 y-yMedia (y-Ymedia)^21 1.10 -0.104 0.01 -2.81 7.91
4.8 1.20 0.001 0.00 -2.61 6.8316.2 1.63 0.166 0.03 -2.01 4.05
40 2.41 0.092 0.01 -1.31 1.7290 3.52 0.079 0.01 -0.21 0.05
169.2 4.97 -0.273 0.07 0.89 0.79323.4 6.76 -0.165 0.03 2.79 7.77582.4 8.90 0.204 0.04 5.29 27.96
1227 30.50 0.0000000 0.20 0.00 57.07SSE SSY
yMedia 3.8125
ECUACION
NCnivel de confianza 95 %
Cuando F calculado es mayor que f critico se rechaza Ho.cuando F calculado es menor que f criticoHo no sirve y nos servirael modelo anterior es decirel modelo lineal.
(yEstimado-yMedia)^27.346.834.751.970.091.358.72
25.84
56.87SSY-SSE
Cuando F calculado es mayor que f critico se rechaza Ho.cuando F calculado es menor que f criticoHo no sirve y nos servirael modelo anterior es decirel modelo lineal.
