Challenges of No-Hypothesis Significance Testing

No-hypothesis significance testing is commonly used in marketing and other fields, but it faces substantial criticism for its binary approach to interpreting data. The practice determines significance based solely on a p-value of 0.05, leading to classifications of results as either significant or non-significant. Critics argue that this oversimplification disregards the complexity of research findings, as single studies cannot definitively prove the existence or absence of an effect. The authors of a forthcoming paper emphasize the need to report results in a more nuanced manner, recognizing that cumulative evidence from multiple studies is essential for drawing reliable conclusions.