Answer:
The type II error might have been committed because of small sample size or small significance level.
Explanation:
A type II error is a statistical word used within the circumstance of hypothesis testing that defines the error that take place when one is unsuccessful to discard a null hypothesis that is truly false. It is symbolized by β i.e.
β = Probability of accepting H₀ when H₀ is false.
In this case we need to test the hypothesis whether the new advertising campaign increases the sales or not.
The hypothesis can be defined as:
H₀: The new advertising campaign does not increases the sales.
Hₐ: The new advertising campaign increases the sales.
The confidence level wanted here is 99%.
The type II error will be made if we conclude that the new advertising campaign does not increases the sales when in fact the sales are increased after the advertising campaign.
The type II error could have been made because of the following reasons:
- The sample size selected is too small. The smaller the sample size, greater is the probability of type II error.
- Significance level of the test must be small. If the significance level is small then the rejection regions decreases. Thus, reducing the chances of correctly rejecting the null hypothesis.
Thus, the type II error might have been committed because of small sample size or small significance level.