Bachiller

VELOCIDAD
Linear model Poly2:
f(x) = p1*x^2 + p2*x + p3
Coefficients (with 95% confidence bounds):
p1 = -0.5043 (-1.3, 0.2912)
p2 = 9.082 (1.287, 16.88)
p3= -15.83 (-31.7, 0.03239)

Goodness of fit:
SSE: 0.1283
R-square: 0.9996
Adjusted R-square: 0.9988
RMSE: 0.3582
ACELERACION
Linear model Poly2:
f(x) = p1*x^2 + p2*x + p3Coefficients (with 95% confidence bounds):
p1 = 2.214e-007 (-5.818e-007, 1.025e-006)
p2 = -1.009 (-1.009, -1.009)
p3 = 9.082 (9.082, 9.082)

Goodness of fit:SSE: 8.308e-011
R-square: 1
Adjusted R-square: 1
RMSE: 3.223e-006

SEGUNDA VELOCIDAD
Linear model Poly3:
f(x) = p1*x^3 + p2*x^2 + p3*x + p4
Coefficients (with 95% confidencebounds):
p1 = -0.03566 (-0.1576, 0.0863)
p2 = 1.482 (-4.974, 7.938)
p3 = -15.71 (-127.5, 96.05)
p4 = 62.69 (-567.5, 692.9)

Goodness of fit:SSE: 0.122
R-square: 0.9997
Adjusted R-square: 0.999
RMSE: 0.3493
ACELERACION DE SEGUNDA
……………
VELOCIDAD TERCERA
Warnings during fitting:
Equation is badly conditioned. Remove repeated datapoints
or try centering and scaling.

Linear model Poly4:
f(x) = p1*x^4 + p2*x^3 + p3*x^2 + p4*x + p5
Coefficients:
p1 = 0.1894
p2 = -19.88
p3 =781.2
p4 = -1.361e+004
p5 = 8.873e+004

Goodness of fit:
SSE: 7.074e-020
R-square: 1
Adjusted R-square: NaN
RMSE: NaN
ACELERACION TERCERA
Linear model Poly3:f(x) = p1*x^3 + p2*x^2 + p3*x + p4
Coefficients (with 95% confidence bounds):
p1 = 0.7576 (0.7576, 0.7576)
p2 = -59.65 (-59.65, -59.65)
p3 = 1562 (1562,1562)
p4 = -1.361e+004 (-1.361e+004, -1.361e+004)

Goodness of fit:
SSE: 1.119e-010
R-square: 1
Adjusted R-square: 1
RMSE: 3.998e-006

VELOCIDAD CUARTA
Linear model Poly2:...