Answer:
See explanation below
Step-by-step explanation:
It depends on what null hypothesis is under consideration.
One of the most common null hypothesis that are subject of study in a given statistical model is <em>the mean</em> predicted by the model.
In this case, the scientist probably observed that the mean of tusk lengths she obtained in a sample did not match the one predicted with the H-W equation.
So, she decided to perform a statistical study by collecting random samples and measuring the tusk lengths to determine a new possible mean and contrast it against the one predicted by the H-W equation.
<em>Let's call M the mean predicted by the H-W equation, and S the mean obtained by the scientist.
</em>
If M different of S and the p-value is 0.021, that means that <em>there is at most 2.1% of probability that the difference between M and S could be due to a random sampling error.
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It should be kept in mind that the p-value does not represent the probability that the scientist is wrong.
(m^2-+1)m^2-1)
M^2 times m^2 gives you m^4
