The correct answer is: A. P
P-value is a statistical measure that is used to determine the probability of obtaining a result at least as extreme as the one that was observed, given that the null hypothesis is true. In other words, it is the probability of getting the results you got, or something even more extreme, if the thing you’re testing (the null hypothesis) is true.
A P-value of less than 0.05 is generally considered to be statistically significant. This means that there is a less than 5% chance that the results you got could have occurred by chance, if the null hypothesis were true.
A P-value is a useful tool for determining whether or not the results of a study are statistically significant. However, it is important to note that a P-value alone does not tell you anything about the size of the effect that you are studying. A small P-value can be obtained for a very small effect, or for a very large effect. To get a sense of the size of the effect, you need to look at the confidence interval.
A confidence interval is a range of values that is likely to contain the true value of the effect that you are studying. The confidence interval is calculated based on the P-value and the sample size. A wider confidence interval indicates that you are less certain about the true value of the effect.
In conclusion, P-value is a useful tool for determining whether or not the results of a study are statistically significant. However, it is important to note that a P-value alone does not tell you anything about the size of the effect that you are studying. To get a sense of the size of the effect, you need to look at the confidence interval.