Final answer:
Hypothesis tests alone are often insufficient for change detection because they may not consider all possible explanations, rely on subjective thresholds of significance, and lack quantitative measures of evidence.
Step-by-step explanation:
The use of hypothesis tests alone is often not sufficient for change detection due to several reasons. First, hypothesis testing relies on the formulation of null and alternative hypotheses, which may not account for all possible explanations or factors influencing the observed data. Second, the threshold probability used to determine statistical significance is often arbitrary and subjective, leading to potential false positives or false negatives. Third, hypothesis testing does not provide quantitative measures of evidence or strength of effect, which can be important in understanding the magnitude and significance of the observed change.