Test Hypotheses with sample of Binomial RV's

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The discussion focuses on testing hypotheses for a binomial distribution with a sample of size n=4, where the null hypothesis H0 states that the mean θ equals 0.5, and the alternative hypothesis H1 states that θ is greater than 0.5. The sample average calculated is Xbar = 1.75, leading to the decision rule to reject H0 if P(Xbar≥1.75) is less than or equal to 0.05. The participant initially calculates a p-value of 0.08146, which is greater than 0.05, suggesting a failure to reject H0. However, upon considering a z-score approach, they find a p-value of 0, which is less than 0.05, indicating that H0 should be rejected.
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Hi, I am trying to teach myself how to test hypotheses for any distribution, but am having some trouble.

X=number chosen each year
θ=Mean number chosen in the population

H0: θ=.5
h1: θ>.5

The random sample of n=4 is 0,1,3,3

Test the Hypotheses at α≤0.05 assuming X is a binomial(5,θ/5).

This is what I have so far, but I feel I am completely missing something..

Sample average (Xbar = 1.75

So,

Reject H0 if P(Xbar≥1.75, given that X is binomial(5,.1)) ≤ 0.05

Then I figure out 1-P(Xbar≤1.75)=0.08146 which is greater than 0.05 so I reject the null.

I know something is not right... Any help would be much appreciated. Thanks!
 
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So would I want to do a z score, like on page three of that document? That seems like it would work better.

Then, I get P(Z≥(1.75-.5)/SQRT(.25/4))=P(Z≥5)=0, which is less than 0.05 so I reject the null..?
 
If that distribution and region corresponds to H0 then yes you reject the null.

Remember that a p-value is looking at a probability for some estimator distribution that relates to a hypothesis.
 
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