Question 1115729
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These two facts should be in your notes:


Fact: A type I error is when you reject the null hypothesis when it is true. The way I remember it is that when you make a type <font color=blue>one</font> error, you are rejecting the <font color=blue>first</font> hypothesis (the null) when it is true, and of course making a mistake in doing so (hence the term "error"). 


Fact: A type II error is when you fail to reject the null and must "accept" the null; however, the reality is that the alternative hypothesis was the true hypothesis. So making a type <font color=blue>two</font> error means you effectively reject the <font color=blue>second</font> hypothesis and make a mistake in doing so.


With that in mind, let's answer the two questions


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First set up the two hypotheses.


Null Hypothesis:
H0: {{{p = 0.32}}}
In English: "The proportion of settled malpractice suits is 0.32"


Alternative Hypothesis:
H1: {{{p <> 0.32}}}
In English: "The proportion of settled malpractice suits is different from 0.32" (aka not equal to 0.32)


If you made a type I error, then you reject H0 (the null) and go with the alternative (H1). But the reality is that H0 was the true hypothesis all along.


So <font color=red>you reject the claim that the proportion of settled malpractice suits is 0.32 when in reality the proportion is 0.32</font>


This means the answer for the first part is <font color=red>Choice D</font>


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For the second part, the answer is <font color=red>Choice A</font>


If you make a type II error, then <font color=red>you fail to reject the claim that the proportion of settled malpractice suits is 0.32, when the proportion is actually different from 0.32</font>


So once again, making a type II error means you go with the null when the alternative is actually the true hypothesis. 

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