Zoologists studying two populations of tigers conducted a two-sample t-test for the difference in means to investigate whether the tigers in population X weigh more, on average, than the tigers in population Y. Two independent random samples were taken, and the difference between the sample means was calculated. All conditions for inference were met, and the test produced a p-value of 0.02.

Which of the following is a correct interpretation of the p-value?

The probability that the mean weight for tigers in population X is greater than that for population Y is 0.02.
A

The probability that the mean weight for tigers in population X is equal to that for population Y is 0.02.
B

Assuming that the mean weights for populations X and Y are equal, the probability of observing a difference equal to the sample difference is 0.02.
C

Assuming that the mean weights for populations X and Y are equal, the probability of observing a difference as great or greater than the sample difference is 0.02.
D

The P-value is indeed the possibility of getting a statistical result that is at least as extreme as the observed result, given that the null hypothesis is true.

The null hypothesis assumes that tiger weight in population X equals tiger weight in population Y.
The alternative hypothesis is that the weight of tigers in population X is higher than that of tigers in population Y.
So, with a p-value of 0.02 for the test, As the proper interpretation of the p-value is If indeed the mean weights of populations X and Y are equal, the probability of seeing a difference equal to or larger than the sample difference is 0.02.

Therefore the final answer is "Option D".

Find out more about the p-value here:

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