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Abstract This paper presents procedures for hypothesis testing and interval estimation for the common mean of several inverse Gaussian populations when the scalar parameters are unknown and unequal.The proposed approaches are based on the concepts of generalized p-value and generalized confidence interval.The simulation results indicate that one of the proposed approaches can provide confidence intervals with good coverage probabilities and can perform hypothesis testing with satisfactory type Ⅰ error probabilities.Furthermore, these approaches can be simply carried out by a few simulation steps.The proposed approaches are illustrated by using two examples.