Let $M_{i}$ and $M^{\\\'}_{i}$ be the maximum and minimum of the $i$th sample from $k$ independent sample with different sample sizes, respectively. Suppose that the survival distribution function of the $i$-th sample is $\\\\bar{F}_i={\\\\bar{F}}^{\\\\alpha_i}$, where $\\\\alpha_i$ is known and positive constant. It is shown that how various exact non-parametric inferential procedures can be developed on the basis of $M_{i}$\\\'s and $M^{\\\'}_{i}$\\\'s for distribution function $F$ without any assumption about it other than $F$ is continuous. These include confidence intervals for quantiles, outer and inner confidence intervals for quantile intervals and upper and lower confidence limits for quantile differences. Three schemes have been investigated and in each case, the associated confidence coefficients are obtained. A numerical example is given in order to illustrate the proposed procedure.

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