We investigate an application of the Tukey's methodology in Theil's regression to obtain a confidence interval for the true slope in the straight line regression model. This specific approach is implemented since 2005 in a package of the software R; however, without any theoretical background. We illustrate by Monte Carlo simulations, that this methodology, unlike the classical Theil's approach based on Kendall's tau, seriously deflates the true confidence level of the resulting interval. We provide also rigorous proofs in case of four data points (in general) and in case of five data points (under uniform distribution of errors). Summing up, we demonstrate that one should never combine statistical methods without checking the assumptions of their usage and we also give a warning to the already wide community of R users of Theil's regression from various fields of science.