Educators are testing a new program designed to help children improve their reading skills. The null hypothesis of the test is that the program does not help children improve their reading skills. For the educators, the more consequential error would be that the program does not help children improve their reading skills but the test indicated that it does help.

Which of the following should the researchers do to avoid the more consequential error?

a. Increase the significance level to increase the probability of Type I error.
b. Increase the significance level to decrease the probability of Type I error.
c. Decrease the significance level to increase the probability of Type I error.
d. Decrease the significance level to decrease the probability of Type I error.
e. Decrease the significance level to decrease the standard error.

To avoid the more consequential error, the researchers should do:
Option D: Decrease the significance level to decrease the probability of Type I error.

What is Type I and Type II error?

Firstly the whole story starts from hypotheses. The null hypothesis is tried to reject and we try to accept the alternate hypothesis.

The type 1 error occurs if we get false positive conclusion (false positive means we accuse null hypothesis being wrong when it was actually correct).
The type 2 error occurs if we get false negative conclusion (false negative means we accept null hypothesis when it was actually false).

The negative is just like the doctor's test getting negative means no disease. Similarly, if we conclude null hypothesis negative means it is accepted. If it is accepted wrongly means the negative test result was false, thus called false negative. This error is called type II error.

How are the type I error and the level of significance of the hypothesis test related?

The probability of committing the type I error is called the significance level of the hypothesis test.

How to find what does researchers should do to avoid more consequential error?

Since in the given context, by using the definitions of the type I error and the type II error, we have

Type I error : False positive : Accepting that the new program does help the children in improving the reading skills when it actually don't.
Type II error: False negative: Failing to reject that the program doesn't help the children in improving the reading skills when it actually improves the skill.

More consequential error for educators : For the educators, the more consequential error would be that the program does not help children improve their reading skills but the test indicated that it does help.

Thus, the more consequential error for the educators is committing the type I error.

To prevent committing this error, they need to decrease type I error's probability which is denoted by level of significance, need to decrease the level of significance of the hypothesis test.

Thus,

Option D: Decrease the significance level to decrease the probability of Type I error.

Lear more about type I and type II error here:
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