In statistical hypothesis testing, the probability and significance value ($\alpha$) work together to help decide whether experimental findings reflect a real effect or just random chance. Basically, in hypothesis testing, the goal is to see if the probability value (p-value) is less than or equal to the significance level (i.e., is $p \le \alpha$). Key Differences between Probability and Significance Value Practical Example of Probability and Significance Value Pre-Experiment: Setting the Significance Value Post-Experiment: Calculating the p-value Making the Decision Exam pass rate Example At a fundamental level, the difference between the probability value and the significance value is: