Critical View on Reliability of One-sample t-Test as a Tool for Business Decision-making

A lot of organizations rely on t-test and hypothesis testing to determine if they can bank on the observation results, they are obtaining, or if it is just unexpected luck or random happenstance. Small businesses find this statistical technique to be an economical and precise way to compare observations or two population groups for numerous different scenarios without resorting to expensive live test scenarios. From testing employee job satisfaction by gender to better understanding economic growth in one city compared to another to identifying if a certain customer segment spends more on specific products, the t-test is a useful statistical technique for businesses. This research suggests a structured analysis aimed to find out the limitations of the one-sample t-test. The results obtained prove that typical characteristics of business processes and the commonly used techniques in empirical research have significant influence on the reliability of the classic one-sample t-test for decision-making, and its nominal error probability is underestimated. In these regards, a set of simple and effective recommendations is given for researchers and decision-makers in order to avoid fatal mistakes in their activities. This piece fills the gap, which is important for further research in economic and managerial statistics.