A marketing consulting group wants to see whether 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 average sales of the seasonal cookie for this region was 650 units. A sample of 36 stores that placed the cookie on an end cap showed a sample mean of 671 units sold with a standard deviation of 81. The resulting p-value is 0.1288; thus, the null hypothesis is not rejected. The marketing consulting group concludes that placing the cookies on an end cap does not affect sales. What type of error is possible in this situation

Question

Alfred

Mathematics

11 March, 16:49

A marketing consulting group wants to see whether 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 average sales of the seasonal cookie for this region was 650 units. A sample of 36 stores that placed the cookie on an end cap showed a sample mean of 671 units sold with a standard deviation of 81. The resulting p-value is 0.1288; thus, the null hypothesis is not rejected. The marketing consulting group concludes that placing the cookies on an end cap does not affect sales. What type of error is possible in this situation

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Destiny Horn · Answer 1

Type II error.

Step-by-step 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.