In the paper multiple testing procedures based on ordered p-values are applied to control type I errors rates for family o f inferences in different statistical problems. Multiple testing procedures based on ordered p-values may be found an interesting tool for simultaneous testing of more than one hypothesis at a time. Discussed methods are applicable to a broad spectrum of statistical problems since their requirements for statistical assumption are considerably less restricted than in case of classical procedures (only dependency among test statistics should be controlled). The analysis is put down to a collection of p-values or adjusted p-values. Depending on approach to the control of Type I error for the family of inferences these methods may be categorized into two major groups: FWE (Family-Wise Error Rate) and FDR (False Discovery Rate) procedures. The procedures of multiple testing are applied to typical situations in economics research: to separate homogenous groups of means, to test the significance of correlation coefficients in the correlation matrix and to infer about significance of regression parameters in linear regression model.