Answer:
Type II error.
Explanation:
We have a hypothesis test for the claim that placing a seasonal cookie product on an end cap (the shelf at the end of an aisle at a store) will make a difference in sales.
The null hypothesis will state that there is no difference, while the alternative hypothesis will state that there is significant positive difference.
The result is a P-value of 0.1288 and the null hypothesis failing to be rejected.
As the null hypothesis failed to be rejected, if an error has been made in the conclusion, is that we erroneusly accept a false null hypothesis.
This is a Type II error, where the null hypothesis is accepted although the alternative hypothesis is true.