Introduction
In this report, we will critically analyze and summarize an interesting research work (Chachi, Taheri, and Viertl) related to testing statistical hypothesis when relevant data and confidence intervals are not precise. In classical Statistical inferences, we state a Null hypothesis about a precise parameter. Then, we test the validity of the Null hypothesis using classical Statistical tests using the concept of confidence intervals at some predefined level x (say 5%) based on uncertainty we can tolerate. If the value of the testing parameter lies in confidence interval 1-x, then the Null hypothesis cannot be rejected. If testing results shows ...
