This chapter addresses the inherent complexities in teaching key terms of statistical inference, exploring the difficulties associated with understanding fundamental concepts such as sampling distribution, confidence intervals, and hypothesis testing. Often, the pedagogical approach focuses more on presenting formulas than on interpretation, resulting in significant gaps in acquired knowledge. In particular, students often find it challenging to comprehend the sample distribution and interpret confidence intervals. Furthermore, confusion continues to exist in hypothesis testing, specifically concerning significance levels and p-values. We would like to emphasise the need for a more integrated and real-world oriented teaching approach that prioritises conceptual understanding over memorisation. The analysis carried out can be taken into account in order to improve teaching performance by offering an opportunity to identify, rectify, and prevent persistent errors.