Most of assignment 20 is stuff you are familiar with. Remember, since the first few questions are about "she knows the standard deviation should" we are still talking about sigma, thus doing z-tests. Try not to get confused! Otherwise, it's just the standard procedure.
Remember the definition for p-value:
"P-value is the probability of getting an x-bar as extreme or more extreme if the null hypothesis were true"
This definition has slightly more things you can see "subbed in" for. Let's try an example.
Let's do the example we talked about in class, the pink cookies from the vending machine. We get an x-bar of 650 calories, and we are testing:
Ho: Mu=600 cal
Ha: Mu>600 cal.
We calculate a p-value of 0.03. If the question asked us to interpret the p-value in context, we might say:
"The probability is 3% of getting a value as high or higher than 650 calories if the true calories of the cookies was 600."
I highlighted the same colors of the sentence that correspond to the definition sentence. See how the main points are there and how you can recognize them? There are obviously different ways to re-arrange the sentence, but all the main parts have to be there.
The last questions (questions 8-11) are what we couldn't go over and you should have learned in class. Just some hints (we will go over what it REALLY means this Thursday.)
A type I error is REJECTING a TRUE null hypothesis.
A type II error is FAILING to REJECT a FALSE null hypothesis.
For example:
Ho: The cake is done.
Ha: The cake is not done.
In a type I error, we REJECT a null hypothesis that was actually TRUE. So, We would say that the cake is not done when the cake was actually done (meaning we left it in the oven and overcooked it).
In a type II error, we would take the cake out, but it wasn't done yet (because we failed to reject the null, but it was false).
alpha=probability of a type I error
beta=probability of a type II error.
I hope that helps you answer the questions, although it contains none of the explanation. I think it will make more sense once we go over it.
Good luck!
-Hillary
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