Answer:
Type I error: Concluded that p ≠ 11% when it is 11%.
Type II error: Concluded that p = 11% when it is not 11%.
Step-by-step explanation:
A <em>type I error</em> is the rejection of the null hypothesis (<em>H₀</em>) when indeed the null hypothesis is true. It is symbolized by <em>α</em>.
A <em>type II error</em> is failing to discard the null hypothesis when indeed the null hypothesis is false. It is symbolized by <em>β</em>.
In this case a principal of a school claims that the percentage of students at his school that come from single-parent homes is 11%.
The hypothesis to test this claim is:
<em>H₀</em>: The proportion of students at the school that come from single-parent homes is 11%, i.e. <em>p</em> = 0.11.
<em>Hₐ</em>: The proportion of students at the school that come from single-parent homes is not 11%, i.e. <em>p</em> ≠ 0.11.
- The type I error will be committed when it is concluded that the proportion of students at the school that come from single-parent homes is not 11% when in fact it is 11%.
- The type II error will be committed when it is concluded that the proportion of students at the school that come from single-parent homes is 11% when it is not.