During today’s class professor speaks about p-value is a crucial tool in hypothesis testing that helps researchers assess the likelihood of observing their data if the null hypothesis is true. It aids in making informed decisions, quantifying evidence, and promoting scientific rigor. However, it should be interpreted alongside effect size and considered within the broader context of research findings to draw meaningful conclusions. The p-value of 52.8 is exceedingly high and far above the commonly used significance level of 0.05 (5%). Typically, in hypothesis testing, if the p-value is less than the chosen significance level (e.g., 0.05), would reject the null hypothesis. However, in this case, with such a high p-value, the null hypothesis of no association between diabetes and inactivity is not rejected, indicating that the two variables are not significantly related in the analyzed data.