Answer: a. p-value
Explanation: The p-value is a statistical degree that shows the opportunity that variations among the determined values and the predicted values are because of random danger alone. In hypothesis testing, the p-value is used to determine whether the results of a study are statistically significant or not. If the p-value is below a predetermined level of significance, typically 0.05 or 0.01, it is considered unlikely that the observed differences are due to chance alone, and the null hypothesis is rejected. On the other hand, if the p-value is above the level of significance, the null hypothesis is not rejected, and the differences observed may be due to chance or other factors. Therefore, the p-value is a crucial statistical measure that allows researchers to draw meaningful conclusions from their data.