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The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β1=β2 =...=βk= 0
The Alternative Hypothesis - H1: Model does fit the data i.e. at least one slope is not equal to zero β1,β2,...,βk ≠ 0
Reject H0 if P-Value ≤ α = 0.05 or F ≥ F?¹'?² = F4'¹5¹4 = 2.37781
Inverse Cumulative Distribution Function
F distribution with 4 DF in numerator and 1514 DF in denominator
P( X <= x ) x
0.95 2.37781
Since F = 134.74 > 2.61078 (CV) we have sufficient evidence to reject H0 at the 5% significant level. Hence we conclude that the goodness of fit model does fit the model. Also since the P-Value = 0.000 < 0.05 we reject H0 as it is highly significant.
PRINCIPLES OF MODELLING IN OR.
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